small fixes to let the package pass R CMD check

DESCRIPTION

@@ -1,24 +1,27 @@
 Package: fisim
 Type: Package
 Title: Forest Inventory Simulator (fisim) is a package for simulating response
-    and samplign designs common in forest inventories.
+    and samplign designs common in forest inventories
 Version: 0.1.0
 Author: Sebastian Schnell, Henning Aberle
 Maintainer: Sebastian Schnell <[email protected]>
 URL: http://github.com/sebschnell/
-Description: The main purpose of the package is to illustrate basic statisitcal
+Description: The main purpose of the package is to illustrate basic statistical
     principles of surveys of environmental resources with a focus on forest
     inventories. The main intention is to use the package in combination with a
     Shiny application to assist teaching in bachelor and master courses on forest
     monitoring.
 License: What license is it under?
 Encoding: UTF-8
 LazyData: true
-Depends: data.table, sp, maptools, spatstat, rgeos
+Depends: R (>= 2.15.1)
 Imports:
+    data.table,
     sp,
     maptools,
     spatstat,
     RANN,
-    rgeos
-RoxygenNote: 6.0.1
+    rgeos,
+    stats,
+    utils
+RoxygenNote: 7.0.2

R/class_definitions.R

@@ -219,20 +219,14 @@ is.tree_pop <- function(x) {
 #'
 #' @param data A \code{\link[data.table]{data.table}} object holding identifiers
 #'   for the sample and respective point locations and row indices that indicate
-#'   which population elements are selected into the sample.
+#'   which population elements are selected into the sample. data must have
+#'   the columns "id_sample", "id_point", "s" and "ef".
 #' @param r_design A \code{character} string indicating the type of the response
 #'   design. One of the following: "fixed_area", "k_tree", "angle_count".
 #' @param r_design_parm A response design specific parameter of type
 #'   \code{numeric}. For "fixed_area" the plot radius in meter; for "k_tree" the
 #'   number of trees closest to the sample location; for "angle_count" the basal
 #'   area factor.
-#' @param ef The expansion factor, i.e., the factor that is used to prorate tree
-#'   attributes to per hectare values (the inverse of the inclusion
-#'   probabilities). Provided by the particular response design functions.
-#' @param ef_alt1 Alternative expansion factor that may be applied when using
-#'   k-tree sampling.
-#' @param ef_alt2 A third alternative expansion factor approximation for k-tree
-#'   sampling
 #'
 #' @details The \code{\link[data.table]{data.table}} object (\code{data}) should
 #'   have the following columns:

R/data.R

@@ -43,3 +43,25 @@
 #'     how often a tree is counted during estimation correcting for edge
 #'     effects, unitless}}
 "hberg_beech"
+
+
+#' Full census of a stand of random trees
+#'
+#' A dataset containing tree stem locations and other attributes of 20000 trees
+#' randomly generated (by ...) on a 1000m by 500m rectangular plot.
+#'
+#' @format An object of class \code{\link{tree_pop}}. The data contains 20000
+#'   rows and 9 columns: \describe{
+#'   \item{id_tree}{Stem number - one tree can have mulitple stems}
+#'   \item{id_stem}{Tree number - repetitions possible due to multiple stems}
+#'   \item{x_tree}{Relative position of the stem center in x-direction}
+#'   \item{y_tree}{Relative position of the stem center in y-direction}
+#'   \item{is_dead}{Was the tree alive or dead?}
+#'   \item{dbh}{Diameter of the stem measured at breast height (1.3m) in cm}
+#'   \item{ba}{Cross-sectional area of the stem at breast height in square
+#'     meters}
+#'   \item{n}{Stem count - helper variable for stem number estimation, unitless}
+#'   \item{f_edge}{Edge factor - helper variable for edge_correction, indicates
+#'     how often a tree is counted during estimation correcting for edge
+#'     effects, unitless}}
+"random_tree"

R/estimation_design.R

@@ -1,6 +1,6 @@
 #' Simple random sampling estimator of population means
 #'
-#' @param data A data.table object with plot-level information of stand
+#' @param point_data A data.table object with plot-level information of stand
 #'   characteristics as coming from the \code{sum_data} function.
 #' @param est_col A character vector of column names for which estimates are
 #'   produced. Used when there is more than one way to expand observations from
@@ -26,7 +26,7 @@ est_srs <- function(point_data, est_col = NULL) {
   dt_est <- point_data$data[,
                             list(est_appr = names(.SD),
                                  y_hat = sapply(.SD, mean),
-                                 v_hat = sapply(.SD, var)/.N),
+                                 v_hat = sapply(.SD, stats::var)/.N),
                             by = list(id_sample, variable),
                             .SDcols = est_col];
   return(dt_est);

R/fisim_package.R

@@ -7,3 +7,9 @@
 #' @docType package
 #' @import data.table spatstat sp rgeos
 NULL
+
+# avoid R CMD check warnings due to global variables
+utils::globalVariables(c("N", "d", "dbh", "ef", "ef_alt1", "ef_alt2", "f_edge",
+                         "id_point", "id_sample", "id_stem", "id_tree",
+                         "is_edge", "n", "n_corr", "s", "variable", "x_s",
+                         "x_tree", "x_wt", "y_s", "y_tree", "y_wt"))

R/sampling_design.R

@@ -69,8 +69,8 @@ xy_sample_random <- function(sp_poly, n, M = 1) {
   y <- unlist(lapply(tri$tiles, function(x) x$bdry[[1]]$y));
 
   s <- sample(length(a), n*M, prob = w, replace = TRUE);
-  r1 <- runif(n*M);
-  r2 <- runif(n*M);
+  r1 <- stats::runif(n*M);
+  r2 <- stats::runif(n*M);
 
   n_vtc <- 3; # Number of vertices in a triangle
   p4_x <- (1 - r1)*x[(s*n_vtc - 2)] + r1*x[(s*n_vtc - 1)];
@@ -137,9 +137,9 @@ xy_sample_regular <- function(sp_poly, n, M = 1, cell_size = NULL, random_rot =
   r_start <- 0L;
   r_end <- 0L;
   if (random_rot) {
-    alpha <- runif(M, min = 0, max = pi);
+    alpha <- stats::runif(M, min = 0, max = pi);
   }
-  u_d <- cbind(runif(M)*d, runif(M)*d);
+  u_d <- cbind(stats::runif(M)*d, stats::runif(M)*d);
   for (m in seq.int(M)) {
     # Enlarge grid to account for possible rotation
     x <- seq(1.5*min(e_cent["x", "min"]) + u_d[m, 1], 1.5*max(e_cent["x", "max"]), d);

R/utilities.R

@@ -1,8 +1,8 @@
 #' Helper function to extract population elements into a sample using a list of
 #' indices
 #'
-#' @param dt_pop The population from which to extract sampled elements.
-#' @param s An integer matrix where rows represent sample locations and columns
+#' @param tree_pop The population from which to extract sampled elements.
+#' @param response An integer matrix where rows represent sample locations and columns
 #'   represent indices of the trees in \code{dt_pop} that are selected at the
 #'   individual sample locations. Zeroes are used to indicate no neighbours and
 #'   to ensure a rectangular data format.
@@ -42,7 +42,7 @@ extract_data <- function(tree_pop, response) {
 #'
 #' @param tree_sample A \code{\link{tree_sample}} object as coming from
 #'   the \code{\link{extract_data}} function.
-#' @param target_var A character vector of variable names which should be
+#' @param target_vars A character vector of variable names which should be
 #'   summarized at the plot level
 #'
 #' @return A data.table object with stand characteristics at the plot level.
@@ -88,7 +88,7 @@ sum_data <- function(tree_sample, target_vars) {
 #'
 #' @param tree_sample A \code{\link{tree_sample}} object as coming from the
 #'   \code{\link{extract_data}} function.
-#' @param target_var A character vector of variable names which should be
+#' @param target_vars A character vector of variable names which should be
 #'   summarized at the plot level
 #'
 #' @details For k-tree sampling, individual tree inlcusion probabilities can
@@ -157,7 +157,7 @@ sum_k_tree <- function(tree_sample, target_vars) {
 #'
 #' @param tree_sample A \code{\link{tree_sample}} object as coming from
 #'   the \code{\link{extract_data}} function.
-#' @param target_var A character vector of variable names which should be
+#' @param target_vars A character vector of variable names which should be
 #'   summarized at the plot level
 #'
 #' @return A data.table object with stand characteristics at the plot level.