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extras

extras provides helper functions for Bayesian analyses.

In particular it provides functions to summarise vectors of MCMC (Monte Carlo Markov Chain) samples, draw random samples from various distributions and calculate deviance residuals as well as R translations of some BUGS (Bayesian Using Gibbs Sampling), JAGS (Just Another Gibbs Sampler), STAN and TMB (Template Model Builder) functions.

Installation

To install the developmental version from GitHub

# install.packages("remotes")
remotes::install_github("poissonconsulting/extras")

Demonstration

Summarise MCMC Samples

The extras package provides functions to summarise MCMC samples like svalue() which gives the surprisal value (Greenland, 2019)

library(extras)
#> 
#> Attaching package: 'extras'
#> The following object is masked from 'package:stats':
#> 
#>     step

set.seed(1)
x <- rnorm(100)
svalue(rnorm(100))
#> [1] 0.3183615
svalue(rnorm(100, mean = 1))
#> [1] 1.704015
svalue(rnorm(100, mean = 2))
#> [1] 3.850857
svalue(rnorm(100, mean = 3))
#> [1] 5.073249

Distributions

Implemented distributions include

R translations

The package also provides R translations of BUGS (and JAGS) functions such as pow() and log<-.

pow(10, 2)
#> [1] 100

mu <- NULL
log(mu) <- 1
mu
#> [1] 2.718282

Numericise R Objects

Atomic vectors, matrices, arrays and data.frames of appropriate classes can be converted to numeric objects suitable for Bayesian analysis using the numericise() (and numericize()) function.

numericise(
  data.frame(logical = c(TRUE, FALSE),
             factor = factor(c("blue", "green")),
             Date = as.Date(c("2000-01-01", "2000-01-02")),
             hms = hms::as_hms(c("00:00:02", "00:01:01"))
  )
)
#>      logical factor  Date hms
#> [1,]       1      1 10957   2
#> [2,]       0      2 10958  61

References

Greenland, S. 2019. Valid P -Values Behave Exactly as They Should: Some Misleading Criticisms of P -Values and Their Resolution With S -Values. The American Statistician 73(sup1): 106–114. https://doi.org/10.1080/00031305.2018.1529625.

Contribution

Please report any issues.

Pull requests are always welcome.

Code of Conduct

Please note that the extras project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

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Version

Install

install.packages('extras')

Monthly Downloads

678

Version

0.6.1

License

MIT + file LICENSE

Issues

Pull Requests

Stars

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Maintainer

Joe Thorley

Last Published

May 10th, 2023

Functions in extras (0.6.1)

extras-package

extras: Helper Functions for Bayesian Analyses
dev_pois_zi

Zero-Inflated Poisson Deviances
dev_neg_binom

Negative Binomial Deviances
dev_student

Student's t Deviances
dev_gamma_pois_zi

Zero-Inflated Gamma-Poisson Deviances
dev_norm

Normal Deviances
log_lik_bern

Bernoulli Log-Likelihood
log<-

Log Transformation
ilogit

Inverse Logistic Transformation
fill_na

Fill Missing Values
invlogit

Inverse Logistic Transformation
dev_lnorm

Log-Normal Deviances
dev_gamma_pois

Gamma-Poisson Deviances
fabs

Absolute
dev_pois

Poisson Deviances
kurtosis

Kurtosis
log_lik_gamma

Gamma Log-Likelihood
log_lik_beta_binom

Beta-Binomial Log-Likelihood
inv_odds

Inverse Odds
log_lik_binom

Binomial Log-Likelihood
inv_logit

Inverse Logistic Transformation
ilog

Inverse Log Transformation
log_lik_gamma_pois_zi

Zero-Inflated Gamma-Poisson Log-Likelihood
logit

Logistic Transformation
numericise

Numericise (or Numericize)
odds<-

Inverse Odds Transformation
log_lik_student

Student's t Log-Likelihood
fill_all

Fill All Values
log_odds_ratio2

Log Odds Ratio2
log_odds_ratio

Log-Odds Ratio
log_lik_pois_zi

Zero-Inflated Poisson Log-Likelihood
log_lik_gamma_pois

Gamma-Poisson Log-Likelihood
log_lik_neg_binom

Negative Binomial Log-Likelihood
proportional_change2

Proportional Change2
params

Parameter Descriptions
phi

Phi
odds_ratio

Odds Ratio
odds

Odds
ran_binom

Binomial Random Samples
proportional_difference

Proportional Difference
ran_beta_binom

Beta-Binomial Random Samples
proportional_difference2

Proportional Difference2
log_odds

Log Odds
log_lik_norm

Normal Log-Likelihood
pvalue

Bayesian P-Value
log_lik_pois

Poisson Log-Likelihood
log_lik_lnorm

Log-Normal Log-Likelihood
pzeros

Proportion of Zeros
par_pattern

Parameter Pattern
proportional_change

Proportional Change
ran_bern

Bernoulli Random Samples
res_beta_binom

Beta-Binomial Residuals
ran_pois_zi

Zero-Inflated Poisson Random Samples
ran_lnorm

Log-Normal Random Samples
ran_student

Student's t Random Samples
log_odds<-

Inverse Log Odds Transformation
logit<-

Logistic Transformation
res_gamma

Gamma Residuals
ran_neg_binom

Negative Binomial Random Samples
res_bern

Bernoulli Residuals
lower

Lower Credible Limit
ran_norm

Normal Random Samples
pextreme

Extreme Probability
res_gamma_pois

Gamma-Poisson Residuals
res_lnorm

Log-Normal Residuals
pow

Power
sextreme

Extreme Surprisal
res_student

Student's t Residuals
res_pois_zi

Zero-Inflated Poisson Residuals
res_neg_binom

Negative Binomial Residuals
res_gamma_pois_zi

Zero-Inflated Gamma-Poisson Residuals
skewness

Skewness
res_pois

Poisson Residuals
odds_ratio2

Odds Ratio2
ran_gamma

Gamma Random Samples
xtr_median

Median
zscore

Z-Score
upper

Upper Credible Limit
step

Step
variance

Variance
xtr_sd

Standard Deviation
zeros

Zeros
svalue

Surprisal Value
ran_gamma_pois

Gamma-Poisson Random Samples
ran_gamma_pois_zi

Zero-Inflated Gamma-Poisson Random Samples
res_binom

Binomial Residuals
res_norm

Normal Residuals
ran_pois

Poisson Random Samples
xtr_mean

Mean
chk_indices

Check Indices
dev_binom

Binomial Deviances
chk_pars

Check Parameter Names
dev_bern

Bernoulli Deviances
chk_index

Check Index
dbern

Bernoulli Distribution
dev_gamma

Gamma Deviances
dev_beta_binom

Beta-Binomial Deviances
as_list_unnamed

As List
as_list

As List