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ChoiceModels change log

0.2.2 (2020-04-17)

  • production release

0.2.2.dev1 (2020-04-14)

  • adds a MergedChoiceTable.from_df() as an alternative constructor

0.2.2.dev0 (2019-04-23)

  • adds a function choicemodels.tools.parallel_lottery_choices() to run iterative lottery choice batches in parallel rather than sequentially

0.2.1 (2019-01-30)

  • fixes a distribution error that excluded the LICENSE.txt file

0.2 (2019-01-25)

  • production release

0.2.dev10 (2019-01-25)

  • moves the choicemodels.tools.distancematrix functions directly into choicemodels.tools

0.2.dev9 (2019-01-22)

  • improves documentation and packaging

0.2.dev8 (2019-01-21)

  • prevents an infinite loop in interative_lottery_choices() when none of the remaining alternatives can accommodate any of the remaining choosers

0.2.dev7 (2018-12-12)

  • adds a check to the MergedChoiceTable constructor to make sure there aren't any column names that overlap between the observations and alternatives tables

0.2.dev6 (2018-11-23)

  • resolves deprecation warnings from older code

  • removes choicemodels.tools.mnl_simulate() (originally from urbansim.urbanchoice.mnl), because this functionality has been fully replaced

  • removes choicemodels.Logit, which wrapped a StatsModels estimator as proof of concept for MNL and didn't provide much value on its own

0.2.dev5 (2018-11-12)

  • adds a chooser_batch_size parameter to iterative_lottery_choices(), to support batch simulation for very large datasets

0.2.dev4 (2018-10-15)

  • adds a function choicemodels.tools.iterative_lottery_choices() for simulation of choices where the alternatives have limited capacity and choosers have varying probability distributions over the alternatives

  • in MergedChoiceTable, empty choosers or alternatives now produces an empty choice table (rather than an exception)

  • adds support for multiple tables of interaction terms in MergedChoiceTable

0.2.dev3 (2018-10-03)

  • adds a function choicemodels.tools.monte_carlo_choices() for efficient simulation of choices for a list of scenarios that have differing probability distributions, but no capacity constraints on the alternatives

0.2.dev2 (2018-09-12)

  • adds a probabilities() method to the MultinomialLogitResults class, which uses the fitted model coefficients to generate predicted probabilities for a table of choice scenarios

  • adds a required model_experssion parameter to the MultinomialLogitResults constructor

0.2.dev1 (2018-08-06)

  • improves the reliability of the native MNL estimator: (a) reduces the chance of a memory overflow when exponentiating utilities and (b) reports warnings from SciPy if the likelihood maximization algorithm may not have converged correctly

  • adds substantial functionality to the MergedChoiceTable utility: sampling of alternatives with or without replacement, alternative-specific weights, interaction weights that apply to combinations of choosers and alternatives, automatic joining of interaction terms onto the merged table, non-sampling (all the alternatives available for each chooser), and estimation/simulation support for all combinations

  • LargeMultinomialLogit class now optionally accepts a MergedChoiceTable as input

0.2.dev0 (2018-07-09)

  • adds additional information to the summary table for the native MNL estimator: number of observations, df of the model, df of the residuals, rho-squared, rho-bar-squared, BIC, AIC, p values, timestamp

0.1.1 (2018-03-08)

  • packaging improvements

0.1 (2018-03-08)

  • initial release