Package: multinomineq 0.2.6

Daniel W. Heck

multinomineq: Bayesian Inference for Multinomial Models with Inequality Constraints

Implements Gibbs sampling and Bayes factors for multinomial models with linear inequality constraints on the vector of probability parameters. As special cases, the model class includes models that predict a linear order of binomial probabilities (e.g., p[1] < p[2] < p[3] < .50) and mixture models assuming that the parameter vector p must be inside the convex hull of a finite number of predicted patterns (i.e., vertices). A formal definition of inequality-constrained multinomial models and the implemented computational methods is provided in: Heck, D.W., & Davis-Stober, C.P. (2019). Multinomial models with linear inequality constraints: Overview and improvements of computational methods for Bayesian inference. Journal of Mathematical Psychology, 91, 70-87. <doi:10.1016/j.jmp.2019.03.004>. Inequality-constrained multinomial models have applications in the area of judgment and decision making to fit and test random utility models (Regenwetter, M., Dana, J., & Davis-Stober, C.P. (2011). Transitivity of preferences. Psychological Review, 118, 42–56, <doi:10.1037/a0021150>) or to perform outcome-based strategy classification to select the decision strategy that provides the best account for a vector of observed choice frequencies (Heck, D.W., Hilbig, B.E., & Moshagen, M. (2017). From information processing to decisions: Formalizing and comparing probabilistic choice models. Cognitive Psychology, 96, 26–40. <doi:10.1016/j.cogpsych.2017.05.003>).

Authors:Daniel W. Heck [aut, cre]

multinomineq_0.2.6.tar.gz
multinomineq_0.2.6.tar.gz(r-4.5-noble)multinomineq_0.2.6.tar.gz(r-4.4-noble)
multinomineq_0.2.6.tgz(r-4.4-emscripten)multinomineq_0.2.6.tgz(r-4.3-emscripten)
multinomineq.pdf |multinomineq.html
multinomineq/json (API)

# Install 'multinomineq' in R:
install.packages('multinomineq', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/danheck/multinomineq/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

2.00 score 4 scripts 283 downloads 42 exports 9 dependencies

Last updated 10 months agofrom:cb972528ce. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 17 2024
R-4.5-linux-x86_64OKNov 17 2024

Exports:Ab_drop_fixedAb_maxAb_multinomAb_sortAb_to_Vadd_fixedbf_binombf_equalitybf_multinombf_nonlinearbinom_to_multinomcount_binomcount_multinomcount_nonlinearcount_to_bfdrop_fixedfind_insideinsideinside_binominside_multinomml_binomml_multinommodel_weightsnirt_to_Abpopulation_bfpostprobppp_binomppp_multinomrpbinomrpdirichletrpmultinomsampling_binomsampling_multinomsampling_nonlinearstochdom_Abstochdom_bfstrategy_marginalstrategy_multiattributestrategy_postprobstrategy_to_Abstrategy_uniqueV_to_Ab

Dependencies:codalatticequadprogRcppRcppArmadilloRcppProgressRcppXPtrUtilsRglpkslam

multinomineq: Multinomial Models with Inequality Constraints

Rendered frommultinomineq_intro.Rmdusingknitr::rmarkdownon Nov 17 2024.

Last update: 2022-11-22
Started: 2019-05-16

Readme and manuals

Help Manual

Help pageTopics
multinomineq: Bayesian Inference for Inequality-Constrained Multinomial Modelsmultinomineq-package multinomineq
Drop fixed columns in the Ab-RepresentationAb_drop_fixed
Automatic Construction of Ab-Representation for Common Inequality ConstraintsAb_max
Get Constraints for Product-Multinomial ProbabilitiesAb_multinom
Sort Inequalities by Acceptance RateAb_sort
Bayes Factor for Linear Inequality Constraintsbf_binom bf_multinom
Bayes Factor with Inequality and (Approximate) Equality Constraintsbf_equality
Bayes Factor for Nonlinear Inequality Constraintsbf_nonlinear count_nonlinear
Converts Binary to Multinomial Frequenciesbinom_to_multinom
Count How Many Samples Satisfy Linear Inequalities (Binomial)count_binom
Count How Many Samples Satisfy Linear Inequalities (Multinomial)count_multinom
Compute Bayes Factor Using Prior/Posterior Countscount_to_bf
Drop or Add Fixed Dimensions for Multinomial Probabilities/Frequenciesadd_fixed drop_fixed
Find a Point/Parameter Vector Within a Convex Polytopefind_inside
Data: Multiattribute Decisions (Heck, Hilbig & Moshagen, 2017)heck2017
Data: Multiattribute Decisions (Heck, Hilbig & Moshagen, 2017)heck2017_raw
Data: Multiattribute Decisions (Hilbig & Moshagen, 2014)hilbig2014
Check Whether Points are Inside a Convex Polytopeinside
Check Whether Choice Frequencies are in Polytopeinside_binom inside_multinom
Data: Item Responses Theory (Karabatsos & Sheu, 2004)karabatsos2004
Maximum-likelihood Estimateml_binom ml_multinom
Get Posterior/NML Model Weightsmodel_weights
Nonparametric Item Response Theory (NIRT)nirt_to_Ab
Aggregation of Individual Bayes Factorspopulation_bf
Transform Bayes Factors to Posterior Model Probabilitiespostprob
Posterior Predictive p-Valuesppp_binom ppp_multinom
Data: Ternary Risky Choices (Regenwetter & Davis-Stober, 2012)regenwetter2012
Random Generation for Independent Multinomial Distributionsrpbinom rpmultinom
Random Samples from the Product-Dirichlet Distributionrpdirichlet
Posterior Sampling for Inequality-Constrained Multinomial Modelssampling_binom sampling_multinom
Posterior Sampling for Multinomial Models with Nonlinear Inequalitiessampling_nonlinear
Ab-Representation for Stochastic Dominance of Histogram Binsstochdom_Ab
Bayes Factor for Stochastic Dominance of Continuous Distributionsstochdom_bf
Log-Marginal Likelihood for Decision Strategystrategy_marginal
Strategy Predictions for Multiattribute Decisionsstrategy_multiattribute
Strategy Classification: Posterior Model Probabilitiesstrategy_postprob
Transform Pattern of Predictions to Polytopestrategy_to_Ab
Unique Patterns/Item Types of Strategy Predictionsstrategy_unique
Strict Weak Order Polytope for 5 Elements and Ternary Choicesswop5
Transform Vertex/Inequality Representation of PolytopeAb_to_V V_to_Ab