multibridge v1.1.0

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Evaluating Multinomial Order Restrictions with Bridge Sampling

Evaluate hypotheses concerning the distribution of multinomial proportions using bridge sampling. The bridge sampling routine is able to compute Bayes factors for hypotheses that entail inequality constraints, equality constraints, free parameters, and mixtures of all three. These hypotheses are tested against the encompassing hypothesis, that all parameters vary freely or against the null hypothesis that all category proportions are equal. For more information see Sarafoglou et al. (2020) <doi:10.31234/osf.io/bux7p>.

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multibridge: Evaluating Multinomial Order Restrictions with Bridge Sampling

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Evaluates hypotheses concerning the distribution of multinomial proportions using bridge sampling. The bridge sampling routine is able to compute Bayes factors for hypotheses that entail inequality constraints, equality constraints, free parameters, and a mix of all three. These hypotheses are tested against the encompassing hypothesis, that all parameters vary freely.

Installation

System requirement is the library mpfr with a version bigger than 3.0.0. To install mpfr, you need a C compiler, preferably GCC. Detailed information on how to install mpfr are available at https://www.mpfr.org/mpfr-current/mpfr.html.

On Mac you can install mpfr through the Terminal (assuming that brew is installed on your machine).

brew install mpfr

On Debian or Ubuntu you can install mpfr through the Terminal:

sudo apt-get install libmpfr-dev

You can install the released version of multibridge from CRAN with:

install.packages("multibridge")

And the development version from GitHub with:

# install.packages("remotes")
remotes::install_github("ASarafoglou/multibridge")

Example

This is a basic example which shows you how to solve a common problem:

library("multibridge")
# data
x <- c(3, 4, 10, 11, 7, 30)
# priors
a <- c(1, 1, 1, 1, 1, 1)
# category labels
factor_levels <- c('theta1', 'theta2', 
                   'theta3', 'theta4', 
                   'theta5', 'theta6')
# constrained hypothesis
Hr            <- c('theta1', '<',  'theta2', '&', 
                   'theta3', '=', 'theta4', ',', 
                   'theta5', '<', 'theta6')
output <- mult_bf_informed(x, Hr, a, factor_levels, seed=2020, niter=2e3)

m1 <- summary(output)
m1
#> Bayes factor analysis
#> 
#>  Hypothesis H_e:
#>  All parameters are free to vary.
#> 
#>  Hypothesis H_r:
#>  theta1 < theta2 & theta3 = theta4 , theta5 < theta6 
#> 
#> Bayes factor estimate LogBFer:
#> 
#> -2.4239
#> 
#> Based on 1 independent equality-constrained hypothesis
#>  and 2 independent inequality-constrained hypotheses. 
#> 
#> Relative Mean-Square Error:
#> 
#> 6.29e-05
#> 
#> Posterior Median and Credible Intervals Of Marginal Beta Distributions:
#>           alpha   beta   2.5%    50% 97.5%
#> 1 theta1 1 + 3  5 + 62 0.0158 0.0522 0.120
#> 2 theta2 1 + 4  5 + 61 0.0236 0.0664 0.140
#> 3 theta3 1 + 10 5 + 55 0.0811 0.1520 0.247
#> 4 theta4 1 + 11 5 + 54 0.0918 0.1660 0.264
#> 5 theta5 1 + 7  5 + 58 0.0507 0.1090 0.195
#> 6 theta6 1 + 30 5 + 35 0.3240 0.4360 0.553

Package dependencies

Functions in multibridge

Name Description
mult_bf_inequality Computes Bayes Factors For Inequality Constrained Multinomial Parameters
journals Prevalence of Statistical Reporting Errors
generate_restriction_list Creates Restriction List Based On User Specified Informed Hypothesis
mult_bf_informed Evaluates Informed Hypotheses on Multinomial Parameters
print.summary.bmult_bridge print method for class summary.bmult_bridge
summary.bmult summary method for class bmult
restriction_list S3 method for class restriction_list.bmult
samples.bmult Extracts prior and posterior samples (if applicable) from an object of class bmult
mult_tsampling Samples From Truncated Dirichlet Density
tbinom_trans Transforms Truncated Beta Samples To Real Line
peas Mendelian Laws of Inheritance
bridge_output.bmult Extracts bridge sampling output from object of class bmult
lifestresses Memory of Life Stresses
mult_bf_equality Computes Bayes Factors For Equality Constrained Multinomial Parameters
tdir_backtrans Backtransforms Samples From Real Line To Dirichlet Parameters
tbinom_backtrans Backtransforms Samples From Real Line To Beta Parameters
print.bmult print method for class bmult
plot.summary.bmult Plot estimates
summary.bmult_bridge summary method for class bmult_bridge
print.bmult_bridge Print method for class bmult_bridge
print.summary.bmult print method for class summary.bmult
samples S3 method for class 'samples.bmult'
restriction_list.bmult Extracts restriction list from an object of class bmult
tdir_trans Transforms Truncated Dirichlet Samples To Real Line
binom_bf_informed Evaluates Informed Hypotheses on Multiple Binomial Parameters
.computeLengthOfRemainingStick Computes Length Of Remaining Stick
binom_bf_equality Computes Bayes Factors For Equality Constrained Binomial Parameters
.adjustUpperBoundForFreeParameters Adjusts Upper Bound For Free Parameters
bridge_output S3 method for class bridge_output.bmult
bayes_factor S3 method for class 'bayes_factor.bmult'
binom_tsampling Samples From Truncated Beta Densities
bayes_factor.bmult Extracts information about computed Bayes factors from object of class bmult
binom_bf_inequality Computes Bayes Factors For Inequality Constrained Independent Binomial Parameters
No Results!

Vignettes of multibridge

Name
MemoryOfLifestresses.Rmd
MendelianLawsOfInheritance.Rmd
PrevalenceOfStatisticalReportingErrors.Rmd
No Results!

Last month downloads

Details

Date 2021-02-19
URL https://github.com/asarafoglou/multibridge/
BugReports https://github.com/asarafoglou/multibridge/issues
License GPL-2
Encoding UTF-8
LazyData true
SystemRequirements GNU make, mpfr (>= 3.0.0)
RoxygenNote 7.1.1
LinkingTo Rcpp
VignetteBuilder knitr
RdMacros Rdpack
NeedsCompilation yes
Packaged 2021-02-22 14:51:05 UTC; alexandra.sarafoglou
Repository CRAN
Date/Publication 2021-02-23 11:10:02 UTC

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