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Examples

# Find the position of the maximum W statistic value in this periodogram (which(res.var2[,2] == max(res.var2[,2])) -1) -#> [1] 114 +#> [1] 118 # "-1" correction at the end of the previous line: the first computed period is T=2, # so period #118 is on line #117 of file res.var2 diff --git a/reference/beta.div.html b/reference/beta.div.html index 1bfeac3..f4d7535 100644 --- a/reference/beta.div.html +++ b/reference/beta.div.html @@ -301,7 +301,7 @@

Examples

g2+g1 } -#> Time for computation = 0.541000 sec +#> Time for computation = 0.466000 sec diff --git a/reference/create.dbMEM.model-1.png b/reference/create.dbMEM.model-1.png index 80b2f9b..b593300 100644 Binary files a/reference/create.dbMEM.model-1.png and b/reference/create.dbMEM.model-1.png differ diff --git a/reference/create.dbMEM.model.html b/reference/create.dbMEM.model.html index 889e798..8f92950 100644 --- a/reference/create.dbMEM.model.html +++ b/reference/create.dbMEM.model.html @@ -167,78 +167,78 @@

Examples

result } -#> dbMEM.1 dbMEM.2 dbMEM.3 dbMEM.4 dbMEM.5 dbMEM.6 -#> S1 -1.0426410 -0.560773845 0.00000000 0.0000000 0.00000000 0.0000000 -#> S2 -1.0405920 -0.564540538 0.00000000 0.0000000 0.00000000 0.0000000 -#> S3 0.5385387 1.714887979 0.00000000 0.0000000 0.00000000 0.0000000 -#> S4 1.2944807 0.006894797 0.00000000 0.0000000 0.00000000 0.0000000 -#> S5 1.0824626 -1.358434905 0.00000000 0.0000000 0.00000000 0.0000000 -#> S6 -0.8322491 0.761966511 0.00000000 0.0000000 0.00000000 0.0000000 -#> S7 0.0000000 0.000000000 0.60367639 -0.1868201 0.00000000 0.0000000 -#> S8 0.0000000 0.000000000 0.60570305 -0.1820122 0.00000000 0.0000000 -#> S9 0.0000000 0.000000000 0.59688978 -0.1755042 0.00000000 0.0000000 -#> S10 0.0000000 0.000000000 -0.95147128 -0.7042591 0.00000000 0.0000000 -#> S11 0.0000000 0.000000000 1.06391594 1.7145220 0.00000000 0.0000000 -#> S12 0.0000000 0.000000000 -1.96793887 1.0626174 0.00000000 0.0000000 -#> S13 0.0000000 0.000000000 0.04922499 -1.5285437 0.00000000 0.0000000 -#> S14 0.0000000 0.000000000 0.00000000 0.0000000 1.45348729 0.6254895 -#> S15 0.0000000 0.000000000 0.00000000 0.0000000 -1.02765443 0.8147607 -#> S16 0.0000000 0.000000000 0.00000000 0.0000000 -1.02787548 0.8144025 -#> S17 0.0000000 0.000000000 0.00000000 0.0000000 -0.09597001 -1.9883616 -#> S18 0.0000000 0.000000000 0.00000000 0.0000000 -0.52333308 -0.5156629 -#> S19 0.0000000 0.000000000 0.00000000 0.0000000 1.22134570 0.2493718 -#> S20 0.0000000 0.000000000 0.00000000 0.0000000 0.00000000 0.0000000 -#> S21 0.0000000 0.000000000 0.00000000 0.0000000 0.00000000 0.0000000 -#> S22 0.0000000 0.000000000 0.00000000 0.0000000 0.00000000 0.0000000 -#> S23 0.0000000 0.000000000 0.00000000 0.0000000 0.00000000 0.0000000 -#> S24 0.0000000 0.000000000 0.00000000 0.0000000 0.00000000 0.0000000 -#> S25 0.0000000 0.000000000 0.00000000 0.0000000 0.00000000 0.0000000 -#> S26 0.0000000 0.000000000 0.00000000 0.0000000 0.00000000 0.0000000 -#> S27 0.0000000 0.000000000 0.00000000 0.0000000 0.00000000 0.0000000 -#> S28 0.0000000 0.000000000 0.00000000 0.0000000 0.00000000 0.0000000 -#> S29 0.0000000 0.000000000 0.00000000 0.0000000 0.00000000 0.0000000 -#> S30 0.0000000 0.000000000 0.00000000 0.0000000 0.00000000 0.0000000 -#> S31 0.0000000 0.000000000 0.00000000 0.0000000 0.00000000 0.0000000 -#> S32 0.0000000 0.000000000 0.00000000 0.0000000 0.00000000 0.0000000 -#> S33 0.0000000 0.000000000 0.00000000 0.0000000 0.00000000 0.0000000 -#> S34 0.0000000 0.000000000 0.00000000 0.0000000 0.00000000 0.0000000 -#> S35 0.0000000 0.000000000 0.00000000 0.0000000 0.00000000 0.0000000 -#> dbMEM.7 dbMEM.8 dbMEM.9 dbMEM.10 -#> S1 0.0000000 0.0000000 0.0000000 0.000000000 -#> S2 0.0000000 0.0000000 0.0000000 0.000000000 -#> S3 0.0000000 0.0000000 0.0000000 0.000000000 -#> S4 0.0000000 0.0000000 0.0000000 0.000000000 -#> S5 0.0000000 0.0000000 0.0000000 0.000000000 -#> S6 0.0000000 0.0000000 0.0000000 0.000000000 -#> S7 0.0000000 0.0000000 0.0000000 0.000000000 -#> S8 0.0000000 0.0000000 0.0000000 0.000000000 -#> S9 0.0000000 0.0000000 0.0000000 0.000000000 -#> S10 0.0000000 0.0000000 0.0000000 0.000000000 -#> S11 0.0000000 0.0000000 0.0000000 0.000000000 -#> S12 0.0000000 0.0000000 0.0000000 0.000000000 -#> S13 0.0000000 0.0000000 0.0000000 0.000000000 -#> S14 0.0000000 0.0000000 0.0000000 0.000000000 -#> S15 0.0000000 0.0000000 0.0000000 0.000000000 -#> S16 0.0000000 0.0000000 0.0000000 0.000000000 -#> S17 0.0000000 0.0000000 0.0000000 0.000000000 -#> S18 0.0000000 0.0000000 0.0000000 0.000000000 -#> S19 0.0000000 0.0000000 0.0000000 0.000000000 -#> S20 1.5343487 0.0000000 0.0000000 0.000000000 -#> S21 -0.6284451 0.0000000 0.0000000 0.000000000 -#> S22 -1.0796112 0.0000000 0.0000000 0.000000000 -#> S23 -0.6446458 0.0000000 0.0000000 0.000000000 -#> S24 0.8183534 0.0000000 0.0000000 0.000000000 -#> S25 0.0000000 -0.3774129 0.0000000 0.000000000 -#> S26 0.0000000 0.7205735 0.0000000 0.000000000 -#> S27 0.0000000 -1.8073283 0.0000000 0.000000000 -#> S28 0.0000000 0.7306073 0.0000000 0.000000000 -#> S29 0.0000000 0.7335603 0.0000000 0.000000000 -#> S30 0.0000000 0.0000000 0.5230897 1.730402441 -#> S31 0.0000000 0.0000000 -1.0367954 -0.571712277 -#> S32 0.0000000 0.0000000 -0.8385537 0.749420473 -#> S33 0.0000000 0.0000000 1.0946391 -1.337973385 -#> S34 0.0000000 0.0000000 1.2943232 0.001741763 -#> S35 0.0000000 0.0000000 -1.0367029 -0.571879015 +#> dbMEM.1 dbMEM.2 dbMEM.3 dbMEM.4 dbMEM.5 dbMEM.6 +#> S1 -0.9454676 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S2 -0.9542209 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S3 1.5685392 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S4 1.1745064 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S5 -0.4131005 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S6 -0.4302566 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S7 0.0000000 1.1914439 -0.7357200 -1.2080015 0.0000000 0.0000000 +#> S8 0.0000000 -0.7418935 1.2170476 0.2661100 0.0000000 0.0000000 +#> S9 0.0000000 -0.8774402 -1.4665890 0.1761710 0.0000000 0.0000000 +#> S10 0.0000000 -0.4963688 1.2048243 -1.5824746 0.0000000 0.0000000 +#> S11 0.0000000 0.6458389 0.8289318 1.6353190 0.0000000 0.0000000 +#> S12 0.0000000 -1.1945640 -0.7871429 0.4125241 0.0000000 0.0000000 +#> S13 0.0000000 1.4729838 -0.2613518 0.3003519 0.0000000 0.0000000 +#> S14 0.0000000 0.0000000 0.0000000 0.0000000 -1.1326073 -0.4355256 +#> S15 0.0000000 0.0000000 0.0000000 0.0000000 -1.3406257 1.4359007 +#> S16 0.0000000 0.0000000 0.0000000 0.0000000 1.0346429 0.6412979 +#> S17 0.0000000 0.0000000 0.0000000 0.0000000 -0.3846593 -1.6171246 +#> S18 0.0000000 0.0000000 0.0000000 0.0000000 0.7713477 -0.6130447 +#> S19 0.0000000 0.0000000 0.0000000 0.0000000 1.0519018 0.5884962 +#> S20 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S21 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S22 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S23 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S24 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S25 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S26 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S27 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S28 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S29 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S30 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S31 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S32 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S33 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S34 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> S35 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 +#> dbMEM.7 dbMEM.8 dbMEM.9 dbMEM.10 +#> S1 0.0000000 0.0000000 0.0000000 0.0000000 +#> S2 0.0000000 0.0000000 0.0000000 0.0000000 +#> S3 0.0000000 0.0000000 0.0000000 0.0000000 +#> S4 0.0000000 0.0000000 0.0000000 0.0000000 +#> S5 0.0000000 0.0000000 0.0000000 0.0000000 +#> S6 0.0000000 0.0000000 0.0000000 0.0000000 +#> S7 0.0000000 0.0000000 0.0000000 0.0000000 +#> S8 0.0000000 0.0000000 0.0000000 0.0000000 +#> S9 0.0000000 0.0000000 0.0000000 0.0000000 +#> S10 0.0000000 0.0000000 0.0000000 0.0000000 +#> S11 0.0000000 0.0000000 0.0000000 0.0000000 +#> S12 0.0000000 0.0000000 0.0000000 0.0000000 +#> S13 0.0000000 0.0000000 0.0000000 0.0000000 +#> S14 0.0000000 0.0000000 0.0000000 0.0000000 +#> S15 0.0000000 0.0000000 0.0000000 0.0000000 +#> S16 0.0000000 0.0000000 0.0000000 0.0000000 +#> S17 0.0000000 0.0000000 0.0000000 0.0000000 +#> S18 0.0000000 0.0000000 0.0000000 0.0000000 +#> S19 0.0000000 0.0000000 0.0000000 0.0000000 +#> S20 -0.4775707 0.0000000 0.0000000 0.0000000 +#> S21 1.3086661 0.0000000 0.0000000 0.0000000 +#> S22 -0.9638916 0.0000000 0.0000000 0.0000000 +#> S23 1.0963046 0.0000000 0.0000000 0.0000000 +#> S24 -0.9635085 0.0000000 0.0000000 0.0000000 +#> S25 0.0000000 1.3079369 0.0000000 0.0000000 +#> S26 0.0000000 -0.9647231 0.0000000 0.0000000 +#> S27 0.0000000 1.0928950 0.0000000 0.0000000 +#> S28 0.0000000 -0.4601915 0.0000000 0.0000000 +#> S29 0.0000000 -0.9759174 0.0000000 0.0000000 +#> S30 0.0000000 0.0000000 -0.6015036 1.7792540 +#> S31 0.0000000 0.0000000 -0.8157037 -0.9796694 +#> S32 0.0000000 0.0000000 -1.0872358 0.2451745 +#> S33 0.0000000 0.0000000 -0.2280320 -1.2049989 +#> S34 0.0000000 0.0000000 1.3136525 -0.3379305 +#> S35 0.0000000 0.0000000 1.4188226 0.4981702 diff --git a/reference/dbmem.html b/reference/dbmem.html index 1e7c50c..dba8653 100644 --- a/reference/dbmem.html +++ b/reference/dbmem.html @@ -220,7 +220,7 @@

Examples

tmp[1:10,1:6] } #> User-provided truncation threshold = 1.012 -#> Time to compute dbMEMs = 0.020000 sec +#> Time to compute dbMEMs = 0.017000 sec diff --git a/reference/envspace.test.html b/reference/envspace.test.html index 0d2267e..f50adb4 100644 --- a/reference/envspace.test.html +++ b/reference/envspace.test.html @@ -314,10 +314,10 @@

Examples

} #> Warning: zero sum general weights #> Procedure stopped (adjR2thresh criteria) adjR2cum = 0.452381 with 11 variables (> 0.446534) +#> Procedure stopped (alpha criteria): pvalue for variable 14 is 0.065000 (> 0.050000) +#> Procedure stopped (alpha criteria): pvalue for variable 14 is 0.079000 (> 0.050000) #> Procedure stopped (alpha criteria): pvalue for variable 14 is 0.068000 (> 0.050000) -#> Procedure stopped (alpha criteria): pvalue for variable 14 is 0.067000 (> 0.050000) -#> Procedure stopped (alpha criteria): pvalue for variable 13 is 0.058000 (> 0.050000) -#> Procedure stopped (alpha criteria): pvalue for variable 16 is 0.070000 (> 0.050000) +#> Procedure stopped (alpha criteria): pvalue for variable 16 is 0.051000 (> 0.050000) #> Monte-Carlo test #> Call: as.randtest(sim = E.b, obs = R2.b, alter = alternative) @@ -329,7 +329,7 @@

Examples

#> Alternative hypothesis: greater #> #> Std.Obs Expectation Variance -#> -2.847141524 0.408750580 0.004609442 +#> -2.809336331 0.408453568 0.004719797 # } diff --git a/reference/forward.sel.html b/reference/forward.sel.html index 9b022d7..051bb6a 100644 --- a/reference/forward.sel.html +++ b/reference/forward.sel.html @@ -193,11 +193,9 @@

Examples

forward.sel(y,x,nperm=99, alpha = 0.5) #> Testing variable 1 #> Testing variable 2 -#> Testing variable 3 -#> Procedure stopped (alpha criteria): pvalue for variable 3 is 0.790000 (> 0.500000) -#> variables order R2 R2Cum AdjR2Cum F pvalue -#> 1 V3 3 0.2869527 0.2869527 0.1978218 3.219452 0.03 -#> 2 V2 2 0.1769297 0.4638824 0.3107060 2.310143 0.10 +#> Procedure stopped (alpha criteria): pvalue for variable 2 is 0.570000 (> 0.500000) +#> variables order R2 R2Cum AdjR2Cum F pvalue +#> 1 V3 3 0.1045178 0.1045178 -0.007417426 0.9337347 0.5 diff --git a/reference/forward.sel.par.html b/reference/forward.sel.par.html index 7ebf153..8f89d77 100644 --- a/reference/forward.sel.par.html +++ b/reference/forward.sel.par.html @@ -182,7 +182,10 @@

Examples

forward.sel.par(y,x, alpha = 0.5) #> The variables in response matrix Y have been standardized -#> Error in forward.sel.par(y, x, alpha = 0.5): Procedure stopped (alpha criterion): pvalue for variable 1 is 0.583931995268155 +#> Procedure stopped (alpha criterion): pvalue for variable 3 is 0.89141 +#> variable order R2 R2cum AdjR2Cum F pval +#> 1 V1 1 0.1225410 0.1225410 0.012858632 1.1172352 0.3667759 +#> 2 V2 2 0.1012978 0.2238388 0.002078469 0.9135791 0.4835534 diff --git a/reference/listw.candidates-1.png b/reference/listw.candidates-1.png index 40e5729..56fcd5c 100644 Binary files a/reference/listw.candidates-1.png and b/reference/listw.candidates-1.png differ diff --git a/reference/listw.candidates-2.png b/reference/listw.candidates-2.png index 959a7e0..c11c416 100644 Binary files a/reference/listw.candidates-2.png and b/reference/listw.candidates-2.png differ diff --git a/reference/listw.candidates-3.png b/reference/listw.candidates-3.png index 40e5729..56fcd5c 100644 Binary files a/reference/listw.candidates-3.png and b/reference/listw.candidates-3.png differ diff --git a/reference/listw.candidates.html b/reference/listw.candidates.html index 2eb2171..f56e7c5 100644 --- a/reference/listw.candidates.html +++ b/reference/listw.candidates.html @@ -214,9 +214,11 @@

Examples

### (binary weighting), or weighted by the linearly decreasing function: candidates <- listw.candidates(coord = xy, nb = c("gab", "mst", "dnear"), weights = c("binary", "flin")) +#> Warning: zero sum general weights +#> Warning: zero sum general weights names(candidates) #> [1] "Gabriel_Binary" "Gabriel_Linear" "MST_Binary" -#> [4] "MST_Linear" "Dnear20.02_Binary" "Dnear20.02_Linear" +#> [4] "MST_Linear" "Dnear17.46_Binary" "Dnear17.46_Linear" plot(candidates[[1]], xy) plot(candidates[[3]], xy) @@ -227,6 +229,11 @@

Examples

### varying between 2 and 5, and a concave-up function with a y parametre of 0.2. candidates2 <- listw.candidates(coord = xy, nb = "dnear", weights = c("fdown", "fup"), y_fdown = 1:5, y_fup = 0.2) +#> Warning: zero sum general weights +#> Warning: zero sum general weights +#> Warning: zero sum general weights +#> Warning: zero sum general weights +#> Warning: zero sum general weights ### Number of spatial weighting matrices generated: length(candidates2) #> [1] 6 diff --git a/reference/listw.select.html b/reference/listw.select.html index 7020445..1e39abb 100644 --- a/reference/listw.select.html +++ b/reference/listw.select.html @@ -299,12 +299,12 @@

Examples

# See Appendix S3 of Bauman et al. 2018 for more extensive examples and illustrations. } -#> Procedure stopped (alpha criteria): pvalue for variable 12 is 0.056667 (> 0.050000) -#> Procedure stopped (adjR2thresh criteria) adjR2cum = 0.938034 with 17 variables (> 0.937661) -#> Procedure stopped (alpha criteria): pvalue for variable 15 is 0.053333 (> 0.050000) -#> Procedure stopped (adjR2thresh criteria) adjR2cum = 0.846676 with 18 variables (> 0.842630) +#> Procedure stopped (alpha criteria): pvalue for variable 13 is 0.086667 (> 0.050000) +#> Procedure stopped (alpha criteria): pvalue for variable 19 is 0.073333 (> 0.050000) +#> Procedure stopped (alpha criteria): pvalue for variable 11 is 0.053333 (> 0.050000) +#> Procedure stopped (adjR2thresh criteria) adjR2cum = 0.858379 with 12 variables (> 0.853796) #> Warning: no non-missing arguments to max; returning -Inf -#> [1] 0.9237376 0.9353406 0.8308033 0.8418676 +#> [1] 0.9346377 0.9497699 0.8670148 0.8512686 # } diff --git a/reference/mfpa-1.png b/reference/mfpa-1.png index 551edf9..d38b3d1 100644 Binary files a/reference/mfpa-1.png and b/reference/mfpa-1.png differ diff --git a/reference/mfpa-3.png b/reference/mfpa-3.png index b7c6f12..a182a40 100644 Binary files a/reference/mfpa-3.png and b/reference/mfpa-3.png differ diff --git a/reference/moran.randtest-1.png b/reference/moran.randtest-1.png index e633bf7..5b36fd4 100644 Binary files a/reference/moran.randtest-1.png and b/reference/moran.randtest-1.png differ diff --git a/reference/msr.4thcorner.html b/reference/msr.4thcorner.html index b82a458..56ee191 100644 --- a/reference/msr.4thcorner.html +++ b/reference/msr.4thcorner.html @@ -175,39 +175,39 @@

Examples

#> --- #> #> Test Stat Obs Std.Obs Alter Pvalue -#> 1 Clay / Lfp r 0.014241856 0.15981546 two-sided 0.88 -#> 2 Silt / Lfp r -0.076256133 -1.11761758 two-sided 0.32 -#> 3 Sand / Lfp r 0.063614861 1.03550793 two-sided 0.32 -#> 4 K2O / Lfp r 0.031979355 0.66201896 two-sided 0.58 -#> 5 Mg++ / Lfp r 0.014982765 0.39901360 two-sided 0.64 -#> 6 Na+/100g / Lfp r 0.093499930 1.24792875 two-sided 0.24 -#> 7 K+ / Lfp r 0.149968927 1.60453877 two-sided 0.06 -#> 8 Conductivity / Lfp r 0.080497038 1.00391888 two-sided 0.34 -#> 9 Retention / Lfp r -0.067943687 -1.07681456 two-sided 0.32 -#> 10 Na+/l / Lfp r 0.063272819 0.85693300 two-sided 0.42 -#> 11 Elevation / Lfp r -0.129537428 -1.42071913 two-sided 0.24 -#> 12 Clay / Min height r 0.061180871 1.43938745 two-sided 0.18 -#> 13 Silt / Min height r -0.052382325 -1.12053462 two-sided 0.3 -#> 14 Sand / Min height r -0.027907397 -0.71329513 two-sided 0.5 -#> 15 K2O / Min height r 0.047550545 1.18431368 two-sided 0.24 -#> 16 Mg++ / Min height r -0.023023055 -0.45527181 two-sided 0.68 -#> 17 Na+/100g / Min height r 0.027191299 0.68827226 two-sided 0.64 -#> 18 K+ / Min height r 0.095029793 1.84674253 two-sided 0.08 -#> 19 Conductivity / Min height r -0.018899856 -0.09870727 two-sided 0.98 -#> 20 Retention / Min height r 0.004165428 0.19270013 two-sided 0.88 -#> 21 Na+/l / Min height r -0.046119268 -0.61815501 two-sided 0.58 -#> 22 Elevation / Min height r 0.061211127 0.98645053 two-sided 0.36 -#> 23 Clay / Max height r 0.010762151 0.32004552 two-sided 0.82 -#> 24 Silt / Max height r -0.030835126 -0.64012989 two-sided 0.56 -#> 25 Sand / Max height r 0.027229507 0.50142089 two-sided 0.58 -#> 26 K2O / Max height r 0.063923177 1.35657708 two-sided 0.14 -#> 27 Mg++ / Max height r 0.010886210 0.35786332 two-sided 0.76 -#> 28 Na+/100g / Max height r 0.026525395 0.60061480 two-sided 0.6 -#> 29 K+ / Max height r 0.109401849 1.75428667 two-sided 0.08 -#> 30 Conductivity / Max height r 0.002446542 0.17629178 two-sided 0.9 -#> 31 Retention / Max height r -0.005456736 -0.12966359 two-sided 0.86 -#> 32 Na+/l / Max height r -0.018577793 -0.29114705 two-sided 0.84 -#> 33 Elevation / Max height r 0.033495574 0.59448183 two-sided 0.56 +#> 1 Clay / Lfp r 0.014241856 0.17412185 two-sided 0.96 +#> 2 Silt / Lfp r -0.076256133 -0.93257080 two-sided 0.46 +#> 3 Sand / Lfp r 0.063614861 0.83587878 two-sided 0.48 +#> 4 K2O / Lfp r 0.031979355 0.19336154 two-sided 0.92 +#> 5 Mg++ / Lfp r 0.014982765 -0.11260277 two-sided 0.92 +#> 6 Na+/100g / Lfp r 0.093499930 0.99271306 two-sided 0.4 +#> 7 K+ / Lfp r 0.149968927 1.24449614 two-sided 0.26 +#> 8 Conductivity / Lfp r 0.080497038 0.89386471 two-sided 0.5 +#> 9 Retention / Lfp r -0.067943687 -0.90342123 two-sided 0.34 +#> 10 Na+/l / Lfp r 0.063272819 0.74188829 two-sided 0.54 +#> 11 Elevation / Lfp r -0.129537428 -1.43071247 two-sided 0.2 +#> 12 Clay / Min height r 0.061180871 0.90379346 two-sided 0.48 +#> 13 Silt / Min height r -0.052382325 -1.12404739 two-sided 0.3 +#> 14 Sand / Min height r -0.027907397 -0.15239979 two-sided 0.92 +#> 15 K2O / Min height r 0.047550545 0.82263178 two-sided 0.42 +#> 16 Mg++ / Min height r -0.023023055 -0.42293738 two-sided 0.68 +#> 17 Na+/100g / Min height r 0.027191299 0.18333160 two-sided 0.84 +#> 18 K+ / Min height r 0.095029793 1.55857112 two-sided 0.14 +#> 19 Conductivity / Min height r -0.018899856 -0.47001633 two-sided 0.66 +#> 20 Retention / Min height r 0.004165428 -0.02712217 two-sided 0.98 +#> 21 Na+/l / Min height r -0.046119268 -0.85124343 two-sided 0.44 +#> 22 Elevation / Min height r 0.061211127 1.04658762 two-sided 0.32 +#> 23 Clay / Max height r 0.010762151 0.08381714 two-sided 0.9 +#> 24 Silt / Max height r -0.030835126 -0.72224712 two-sided 0.56 +#> 25 Sand / Max height r 0.027229507 0.68254101 two-sided 0.56 +#> 26 K2O / Max height r 0.063923177 1.10680220 two-sided 0.28 +#> 27 Mg++ / Max height r 0.010886210 0.15536832 two-sided 0.78 +#> 28 Na+/100g / Max height r 0.026525395 0.19050138 two-sided 0.76 +#> 29 K+ / Max height r 0.109401849 1.45479398 two-sided 0.18 +#> 30 Conductivity / Max height r 0.002446542 -0.30459148 two-sided 0.78 +#> 31 Retention / Max height r -0.005456736 -0.23725075 two-sided 0.86 +#> 32 Na+/l / Max height r -0.018577793 -0.68055282 two-sided 0.5 +#> 33 Elevation / Max height r 0.033495574 0.95380463 two-sided 0.34 #> Pvalue.adj #> 1 1 #> 2 1 diff --git a/reference/msr.html b/reference/msr.html index 8d63060..4bfad6e 100644 --- a/reference/msr.html +++ b/reference/msr.html @@ -177,32 +177,32 @@

Examples

lw1 <- nb2listw(cell2nb(9, 9)) moran.mc(x1[,1], lw1, 2)$statistic -#> statistic -#> -0.03639357 +#> statistic +#> 0.04822633 ## singleton x1.1 <- msr(x1[,1], lw1, nrepet = 9, method = "singleton") apply(x1.1, 2, function(x) moran.mc(x, listw = lw1, nsim = 2)$statistic) -#> [1] -0.03639357 -0.03639357 -0.03639357 -0.03639357 -0.03639357 -0.03639357 -#> [7] -0.03639357 -0.03639357 -0.03639357 +#> [1] 0.04822633 0.04822633 0.04822633 0.04822633 0.04822633 0.04822633 0.04822633 +#> [8] 0.04822633 0.04822633 ## triplet x1.2 <- msr(x1[,1], lw1, nrepet = 9, method = "triplet") apply(x1.2, 2, function(x) moran.mc(x, listw = lw1, nsim = 2)$statistic) -#> [1] -0.03639357 -0.03639357 -0.03639357 -0.03639357 -0.03639357 -0.03639357 -#> [7] -0.03639357 -0.03639357 -0.03639357 +#> [1] 0.04822633 0.04822633 0.04822633 0.04822633 0.04822633 0.04822633 0.04822633 +#> [8] 0.04822633 0.04822633 ## pair x1.3 <- msr(x1[,1], lw1, nrepet = 9, method = "pair") apply(x1.3, 2, function(x) moran.mc(x, listw = lw1, nsim = 2)$statistic) -#> [1] -0.03221325 -0.02994351 -0.03814300 -0.03681758 -0.03739308 -0.03199512 -#> [7] -0.03304550 -0.03573920 -0.03205419 +#> [1] 0.04542902 0.04999278 0.05081998 0.04557723 0.04692956 0.04758979 0.03924947 +#> [8] 0.05050025 0.04447356 ## pair with cor.fixed x1.4 <- msr(x1[,1], lw1, nrepet = 9, cor.fixed = 0.5) apply(x1.4, 2, function(x) moran.mc(x, listw = lw1, nsim = 2)$statistic) -#> [1] -0.03081582 -0.03521671 -0.03645620 -0.03138562 -0.03821900 -0.03679121 -#> [7] -0.03321552 -0.03577997 -0.03207838 +#> [1] 0.04592704 0.04526796 0.03830314 0.04709447 0.04439314 0.03914596 0.03982563 +#> [8] 0.04629397 0.04021874 cor(x1[,1], x1.4) #> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] #> [1,] 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 @@ -210,178 +210,178 @@

Examples

## pair preserving correlations for multivariate data x1.5 <- msr(x1, lw1, nrepet = 9, cor.fixed = 0.5) cor(x1) -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 lapply(x1.5, cor) #> [[1]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> #> [[2]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> #> [[3]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> #> [[4]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> #> [[5]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> #> [[6]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> #> [[7]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> #> [[8]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> #> [[9]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> apply(x1, 2, function(x) moran.mc(x, listw = lw1, nsim = 2)$statistic) -#> [1] -0.036393570 0.003795524 -0.125770324 -0.108078457 0.011237403 +#> [1] 0.04822633 0.02110687 0.10728771 -0.09992192 -0.05342812 apply(x1.5[[1]], 2, function(x) moran.mc(x, listw = lw1, nsim = 2)$statistic) -#> [1] -0.030109453 0.002228235 -0.116894243 -0.105638622 0.015747495 +#> [1] 0.04802965 0.02083488 0.10791366 -0.10425508 -0.05269660 ## singleton preserving correlations for multivariate data x1.6 <- msr(x1, lw1, nrepet = 9, method = "singleton") cor(x1) -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 lapply(x1.6, cor) #> [[1]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> #> [[2]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> #> [[3]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> #> [[4]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> #> [[5]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> #> [[6]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> #> [[7]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> #> [[8]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> #> [[9]] -#> [,1] [,2] [,3] [,4] [,5] -#> [1,] 1.00000000 0.08956080 0.35454684 -0.11295047 -0.00366931 -#> [2,] 0.08956080 1.00000000 -0.03499248 0.02751043 -0.11022267 -#> [3,] 0.35454684 -0.03499248 1.00000000 -0.06411345 0.03575739 -#> [4,] -0.11295047 0.02751043 -0.06411345 1.00000000 -0.06091456 -#> [5,] -0.00366931 -0.11022267 0.03575739 -0.06091456 1.00000000 +#> [,1] [,2] [,3] [,4] [,5] +#> [1,] 1.00000000 0.02666787 0.08030075 0.20071390 0.08508976 +#> [2,] 0.02666787 1.00000000 0.05922744 -0.05458306 0.02194467 +#> [3,] 0.08030075 0.05922744 1.00000000 -0.01711083 0.14292552 +#> [4,] 0.20071390 -0.05458306 -0.01711083 1.00000000 0.03194435 +#> [5,] 0.08508976 0.02194467 0.14292552 0.03194435 1.00000000 #> apply(x1, 2, function(x) moran.mc(x, listw = lw1, nsim = 2)$statistic) -#> [1] -0.036393570 0.003795524 -0.125770324 -0.108078457 0.011237403 +#> [1] 0.04822633 0.02110687 0.10728771 -0.09992192 -0.05342812 apply(x1.6[[1]], 2, function(x) moran.mc(x, listw = lw1, nsim = 2)$statistic) -#> [1] -0.036393570 0.003795524 -0.125770324 -0.108078457 0.011237403 +#> [1] 0.04822633 0.02110687 0.10728771 -0.09992192 -0.05342812 diff --git a/reference/msr.mantelrtest.html b/reference/msr.mantelrtest.html index 3749d57..b000228 100644 --- a/reference/msr.mantelrtest.html +++ b/reference/msr.mantelrtest.html @@ -153,11 +153,11 @@

Examples

#> Observation: 0.1197583 #> #> Based on 999 replicates -#> Simulated p-value: 0.207 +#> Simulated p-value: 0.168 #> Alternative hypothesis: greater #> #> Std.Obs Expectation Variance -#> 0.746684848 0.050906679 0.008502644 +#> 0.945357137 0.041287048 0.006890165 diff --git a/reference/msr.varipart.html b/reference/msr.varipart.html index ff31014..ac5c4c7 100644 --- a/reference/msr.varipart.html +++ b/reference/msr.varipart.html @@ -166,7 +166,7 @@

Examples

#> Alternative hypothesis: greater #> #> Std.Obs Expectation Variance -#> 2.6146724878 0.1746737065 0.0005619428 +#> 2.4022539087 0.1766632394 0.0006236644 #> #> Individual fractions: #> a b c d @@ -174,7 +174,7 @@

Examples

#> #> Adjusted fractions: #> a b c d -#> -0.01181311 0.08691272 0.25912501 0.66577538 +#> -0.01386611 0.08673077 0.25930696 0.66782838 diff --git a/reference/mst.nb-1.png b/reference/mst.nb-1.png index b7b7ebf..4953bf9 100644 Binary files a/reference/mst.nb-1.png and b/reference/mst.nb-1.png differ diff --git a/reference/ortho.AIC.html b/reference/ortho.AIC.html index 1fddc6d..7703002 100644 --- a/reference/ortho.AIC.html +++ b/reference/ortho.AIC.html @@ -129,24 +129,24 @@

Examples

nvar <- length(1:minAIC)+1 # number of orthogonal vectors + 1 for intercept lm1 <- lm(y~x[,res$ord[1:minAIC]]) summary(lm1)$r.squared # R2 -#> [1] 0.8310555 +#> [1] 0.7941018 res$R2[minAIC] # the same -#> [1] 0.8310555 +#> [1] 0.7941018 min(res$AICc) # corrected AIC -#> [1] -78.7284 +#> [1] -82.02489 extractAIC(lm1) # classical AIC -#> [1] 5.00000 -80.09203 +#> [1] 5.00000 -83.38853 min(res$AICc)-2*(nvar*(nvar+1))/(nrow(x)-nvar-1) # the same -#> [1] -80.09203 +#> [1] -83.38853 lm2 <- lm(y~1) res$AICc0 # corrected AIC for the null model -#> [1] 0.9005399 +#> [1] -12.28652 extractAIC(lm2) # classical AIC -#> [1] 1.0000000 0.8172066 +#> [1] 1.00000 -12.36985 res$AICc0-2*(1*(1+1))/(nrow(x)-1-1) # the same -#> [1] 0.8172066 +#> [1] -12.36985 diff --git a/reference/rotation-1.png b/reference/rotation-1.png index d669b94..3506093 100644 Binary files a/reference/rotation-1.png and b/reference/rotation-1.png differ diff --git a/reference/rotation-10.png b/reference/rotation-10.png index 8fa36d1..6084d6e 100644 Binary files a/reference/rotation-10.png and b/reference/rotation-10.png differ diff --git a/reference/rotation-11.png b/reference/rotation-11.png index aa939aa..15d7fb0 100644 Binary files a/reference/rotation-11.png and b/reference/rotation-11.png differ diff --git a/reference/rotation-12.png b/reference/rotation-12.png index 4f2f110..d9b28e5 100644 Binary files a/reference/rotation-12.png and b/reference/rotation-12.png differ diff --git a/reference/rotation-13.png b/reference/rotation-13.png index bf1f27e..6a52395 100644 Binary files a/reference/rotation-13.png and b/reference/rotation-13.png differ diff --git a/reference/rotation-14.png b/reference/rotation-14.png index 1e7d5b5..b7f2724 100644 Binary files a/reference/rotation-14.png and b/reference/rotation-14.png differ diff --git a/reference/rotation-15.png b/reference/rotation-15.png index 8a871ef..5f3e6ab 100644 Binary files a/reference/rotation-15.png and b/reference/rotation-15.png differ diff --git a/reference/rotation-16.png b/reference/rotation-16.png index 5d71330..3a9cc46 100644 Binary files a/reference/rotation-16.png and b/reference/rotation-16.png differ diff --git a/reference/rotation-17.png b/reference/rotation-17.png index 53d156f..13f4660 100644 Binary files a/reference/rotation-17.png and b/reference/rotation-17.png differ diff --git a/reference/rotation-18.png b/reference/rotation-18.png index 4f3d94a..a133c97 100644 Binary files a/reference/rotation-18.png and b/reference/rotation-18.png differ diff --git a/reference/rotation-19.png b/reference/rotation-19.png index 62f3012..7b6fe44 100644 Binary files a/reference/rotation-19.png and b/reference/rotation-19.png differ diff --git a/reference/rotation-2.png b/reference/rotation-2.png index eb27ce6..10b1e6e 100644 Binary files a/reference/rotation-2.png and b/reference/rotation-2.png differ diff --git a/reference/rotation-20.png b/reference/rotation-20.png index 9e2668b..684e2ae 100644 Binary files a/reference/rotation-20.png and b/reference/rotation-20.png differ diff --git a/reference/rotation-21.png b/reference/rotation-21.png index 07992a0..26028d1 100644 Binary files a/reference/rotation-21.png and b/reference/rotation-21.png differ diff --git a/reference/rotation-3.png b/reference/rotation-3.png index 68b2f5e..59549c1 100644 Binary files a/reference/rotation-3.png and b/reference/rotation-3.png differ diff --git a/reference/rotation-4.png b/reference/rotation-4.png index ce35ef4..f25d791 100644 Binary files a/reference/rotation-4.png and b/reference/rotation-4.png differ diff --git a/reference/rotation-5.png b/reference/rotation-5.png index e2203a3..7cb2207 100644 Binary files a/reference/rotation-5.png and b/reference/rotation-5.png differ diff --git a/reference/rotation-6.png b/reference/rotation-6.png index c85a100..651e357 100644 Binary files a/reference/rotation-6.png and b/reference/rotation-6.png differ diff --git a/reference/rotation-7.png b/reference/rotation-7.png index 1a16081..72b8965 100644 Binary files a/reference/rotation-7.png and b/reference/rotation-7.png differ diff --git a/reference/rotation-8.png b/reference/rotation-8.png index 60c6252..fc493fb 100644 Binary files a/reference/rotation-8.png and b/reference/rotation-8.png differ diff --git a/reference/rotation-9.png b/reference/rotation-9.png index 3011d6b..f9d707b 100644 Binary files a/reference/rotation-9.png and b/reference/rotation-9.png differ diff --git a/reference/rotation.html b/reference/rotation.html index 16c387b..c731785 100644 --- a/reference/rotation.html +++ b/reference/rotation.html @@ -124,27 +124,27 @@

Examples

### Rotate the coordinates by an angle of 90 degrees coords.90<-rotation(coords,90*pi/180) coords.90 -#> [,1] [,2] -#> [1,] -0.28374728 0.98923920 -#> [2,] -0.04633513 0.39377011 -#> [3,] -0.01377965 0.05113566 -#> [4,] -0.51962734 0.46812314 -#> [5,] -0.84724666 0.06252493 -#> [6,] -0.22623976 0.89712233 -#> [7,] -0.05130279 0.08959023 -#> [8,] -0.82374271 0.27166667 -#> [9,] -0.15504513 0.70649633 -#> [10,] -0.32467674 0.26759735 -#> [11,] -0.42556442 0.17219251 -#> [12,] -0.21220240 0.03810026 -#> [13,] -0.42789429 0.61548212 -#> [14,] -0.49993821 0.79052511 -#> [15,] -0.51375854 0.52703084 -#> [16,] -0.99336227 0.74967838 -#> [17,] -0.12121028 0.65250327 -#> [18,] -0.07505957 0.58096035 -#> [19,] -0.37882504 0.06843743 -#> [20,] -0.65982190 0.08314040 +#> [,1] [,2] +#> [1,] -0.14015316 0.2023632 +#> [2,] -0.24702232 0.5547860 +#> [3,] -0.52711471 0.7718177 +#> [4,] -0.21694820 0.3090707 +#> [5,] -0.65334653 0.5601560 +#> [6,] -0.31644873 0.3827721 +#> [7,] -0.90174585 0.4008919 +#> [8,] -0.40571365 0.6887974 +#> [9,] -0.11812040 0.9202164 +#> [10,] -0.11840440 0.8238224 +#> [11,] -0.39643877 0.4481312 +#> [12,] -0.14906824 0.2522923 +#> [13,] -0.09397533 0.4503928 +#> [14,] -0.35202367 0.5406376 +#> [15,] -0.35137065 0.7015736 +#> [16,] -0.90838867 0.9075445 +#> [17,] -0.61649471 0.5263501 +#> [18,] -0.06788685 0.1608651 +#> [19,] -0.48249527 0.3618554 +#> [20,] -0.19237050 0.5209074 plot(coords,xlim=range(rbind(coords.90,coords)[,1]),ylim=range(rbind(coords.90,coords)[,2]),asp=1) points(coords.90,pch=19) diff --git a/reference/stimodels.html b/reference/stimodels.html index 3d55355..168e30d 100644 --- a/reference/stimodels.html +++ b/reference/stimodels.html @@ -351,7 +351,7 @@

Examples

#> Time test: R2 = 0.3076 F = 22.0858 P( 99 perm) = 0.01 #> #> ------------------------------------------------------- -#> Time for computation = 1.159000 sec +#> Time for computation = 0.785000 sec #> ======================================================= #> @@ -419,7 +419,7 @@

Examples

#> Time test: R2 = 0.5265 F = 3.4186 P( 999 perm) = 0.001 #> #> --------------------------------------------------------- -#> Time for computation = 4.264000 sec +#> Time for computation = 3.662000 sec #> ========================================================= #> @@ -464,7 +464,7 @@

Examples

#> Number of interaction variables = 10 #> Number of residual degrees of freedom = 11 #> -#> Interaction test: R2 = 0.0755 F = 1.1814 P( 999 perm) = 0.243 +#> Interaction test: R2 = 0.0755 F = 1.1814 P( 999 perm) = 0.216 #> --------------------------------------------------------------------- #> Testing for common spatial and common temporal structures (model 5) #> --------------------------------------------------------------------- @@ -473,7 +473,7 @@

Examples

#> Time test: R2 = 0.045 F = 7.045 P( 999 perm) = 0.001 #> #> --------------------------------------------------------- -#> Time for computation = 0.724000 sec +#> Time for computation = 0.560000 sec #> ========================================================= #> @@ -513,7 +513,7 @@

Examples

#> Number of interaction variables = 10 #> Number of residual degrees of freedom = 11 #> -#> Interaction test: R2 = 0.1476 F = 1.5921 P( 999 perm) = 0.014 +#> Interaction test: R2 = 0.1476 F = 1.5921 P( 999 perm) = 0.011 #> ---------------------------------------------------- #> Testing for separate spatial structures (model 6a) #> ---------------------------------------------------- @@ -534,7 +534,7 @@

Examples

#> Model 6b requires that 'tt' be larger than 2. When tt=2, full coding of the times by a binary variable or Helmert contrast does not leave any degree of freedom for the residuals in the test of the Time factor. #> #> --------------------------------------------------------- -#> Time for computation = 0.837000 sec +#> Time for computation = 0.641000 sec #> ========================================================= #> @@ -584,7 +584,7 @@

Examples

#> Time test: R2 = 0.3076 F = 22.0858 P( 999 perm) = 0.001 #> #> ------------------------------------------------------- -#> Time for computation = 2.474000 sec +#> Time for computation = 2.047000 sec #> ======================================================= #> @@ -631,7 +631,7 @@

Examples

#> Time test: R2 = 0.3076 F = 18.8093 P( 999 perm) = 0.001 #> #> ------------------------------------------------------- -#> Time for computation = 2.978000 sec +#> Time for computation = 2.459000 sec #> ======================================================= #> @@ -674,7 +674,7 @@

Examples

#> Time test: R2 = 0.3076 F = 18.8093 P( 999 perm) = 0.001 #> #> ------------------------------------------------------- -#> Time for computation = 2.420000 sec +#> Time for computation = 2.063000 sec #> ======================================================= #> diff --git a/reference/tpaired.randtest.html b/reference/tpaired.randtest.html index ae45e38..2313f02 100644 --- a/reference/tpaired.randtest.html +++ b/reference/tpaired.randtest.html @@ -144,7 +144,7 @@

Examples

#> Degrees of freedom: 9 #> Alternative hypothesis: two.sided #> Prob (parametric): 0.007703223 -#> Prob ( 99 permutations): 0.03000 +#> Prob ( 99 permutations): 0.04000 ## Compare the results to: res2 = t.test(deer[,1], deer[,2], paired=TRUE)