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On the recordRead 12 Oct 202620 facts
R-fitODBOD
On the record
- Data preparation
- The BODextract function can prepare raw binomial outcome data in the frequency format used in the examples.amalan-constat.github.io · read 12 Oct 2026
- Dependencies
- The beta-binomial example uses mle2 from the bbmle package for maximum-likelihood estimation.amalan-constat.github.io · read 12 Oct 2026
- Distribution families
- The package lists six alternate binomial distributions and eight binomial mixture distributions.amalan-constat.github.io · read 12 Oct 2026
- Estimation
- The package documentation describes maximum likelihood and method of moments approaches for estimating distribution parameters.amalan-constat.github.io · read 12 Oct 2026
- Example data
- The site demonstrates the workflow with alcohol consumption data from 399 respondents in the Netherlands in 1983.amalan-constat.github.io · read 12 Oct 2026
- Example dataset
- The modeling example uses alcohol-consumption data from 399 respondents in the Netherlands in 1983.amalan-constat.github.io · read 12 Oct 2026
- Input format
- The modeling walkthrough says its later steps can be applied when the dataset is in frequency-table form.amalan-constat.github.io · read 12 Oct 2026
- Installation
- The maker’s site gives installation instructions for both GitHub and CRAN.amalan-constat.github.io · read 12 Oct 2026
- License
- The package is listed under the GPL-2 license.amalan-constat.github.io · read 12 Oct 2026
- Maintainers
- The project page names Amalan Mahendran as author and maintainer and Pushpakanthie Wijekoon as author and contributor.amalan-constat.github.io · read 12 Oct 2026
- Model fitting
- Fitting functions can report expected frequencies, chi-squared statistics, p-values, and degrees of freedom for assessing fit.amalan-constat.github.io · read 12 Oct 2026
- Modeling criteria
- Its example compares candidate distributions using p-values, negative log-likelihood, AIC, observed and expected frequency differences, and variance differences.amalan-constat.github.io · read 12 Oct 2026
- Model selection
- The documentation recommends comparing p-values, negative log likelihood, AIC, frequency differences, and variance differences when selecting a fit.amalan-constat.github.io · read 12 Oct 2026
- Notable limit
- The example says steps 2 through 5 can be applied only when the dataset is in frequency-table form.amalan-constat.github.io · read 12 Oct 2026
- Overdispersion
- The package describes binomial mixture distributions as useful for fitting overdispersed binomial outcome data.amalan-constat.github.io · read 12 Oct 2026
- Purpose
- fitODBOD models binomial outcome data using binomial mixture and alternate binomial distributions.amalan-constat.github.io · read 12 Oct 2026
- R Shiny application
- The maker says fitODBODRshiny is available to fit selected binomial outcome data using binomial mixture and alternate binomial distributions.amalan-constat.github.io · read 12 Oct 2026
- Scripting support
- Yesamalan-constat.github.io · read 23 Sep 2026
