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multinomineq
View on CRAN: Click
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Download and install multinomineq package within the R console
Install from CRAN:
install.packages("multinomineq")
Install from Github:
library("remotes")
install_github("cran/multinomineq")
Install by package version:
library("remotes")
install_version("multinomineq", "0.2.6")
Attach the package and use:
library("multinomineq")
Maintained by
Daniel W. Heck
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.multinomineq . https://github.com/danheck/multinomineq . multinomineq citation info . multinomineq results . multinomineq.pdf . multinomineq: Multinomial Models with Inequality Constraints . multinomineq_0.2.6.tar.gz . multinomineq_0.2.6.zip . multinomineq_0.2.6.zip . multinomineq_0.2.6.zip . multinomineq_0.2.6.tgz . multinomineq_0.2.6.tgz . multinomineq_0.2.6.tgz . multinomineq_0.2.6.tgz . multinomineq_0.2.6.tgz . multinomineq_0.2.6.tgz . multinomineq archive . https://CRAN.R-project.org/package=multinomineq .
First Published: 2019-05-16
Latest Update: 2024-02-20
Description:
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. .
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
How to cite:
Daniel W. Heck (2019). multinomineq: Bayesian Inference for Multinomial Models with Inequality Constraints. R package version 0.2.6, https://cran.r-project.org/web/packages/multinomineq. Accessed 08 Apr. 2025.
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Complete documentation for multinomineq
Functions, R codes and Examples using
the multinomineq R package
Some associated functions: Ab_drop_fixed . Ab_max . Ab_multinom . Ab_sort . V_to_Ab . bf_binom . bf_equality . bf_nonlinear . binom_to_multinom . count_binom . count_multinom . count_to_bf . drop_fixed . find_inside . heck2017 . heck2017_raw . hilbig2014 . inside . inside_binom . karabatsos2004 . ml_binom . model_weights . multinomineq-package . nirt_to_Ab . population_bf . postprob . ppp_binom . regenwetter2012 . rpbinom . rpdirichlet . sampling_multinom . sampling_nonlinear . stochdom_Ab . stochdom_bf . strategy_marginal . strategy_multiattribute . strategy_postprob . strategy_to_Ab . strategy_unique . swop5 .
Some associated R codes: Ab_max.R . RcppExports.R . auxiliary.R . bf_binom.R . bf_equality.R . bf_nonlinear.R . checks.R . classes_ineq.R . conjoint_measurement.R . count_binomial.R . count_multinomial.R . count_nonconvex.R . count_to.R . data_hilbig2014_heck2017.R . data_karabatsos2004.R . data_regenwetter2012.R . data_swop.R . equality_constraints.R . find_inside.R . inside.R . line_clipping.R . ml_estimates.R . model_weights.R . multinomineq_package.R . nirt.R . population_bf.R . posterior_predictive.R . postprob.R . rpmultinom.R . run_parallel.R . sampling_nonlinear.R . sampling_polytope.R . sampling_vertex.R . sort_inequalities.R . stochdom_Ab.R . stochdom_bf.R . strategy_marginal.R . strategy_multiattribute.R . strategy_unique.R . transform_Ab_V.R . Full multinomineq package functions and examples
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