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zoib (version 1.3.4)

Bayesian Inference for Beta Regression and Zero-or-One Inflated Beta Regression

Description

Fits beta regression and zero-or-one inflated beta regression and obtains Bayesian Inference of the model via the Markov Chain Monte Carlo approach implemented in JAGS.

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Version

Install

install.packages('zoib')

Monthly Downloads

271

Version

1.3.4

License

GPL (>= 3)

Maintainer

Fang Liu

Last Published

May 21st, 2016

Functions in zoib (1.3.4)

BiRepeated

Data from a correlated bivariate beta distribution with repeated measures
GasolineYield

Gasoline Yields Data
joint.1z1

Jointly modelling of multiple variables taking values from (0,1] when there is a single random variable in the linear predictors of the link functions
joint.1z01

Jointly modelling of multiple variables taking values from [0,1] when there is a single random variable in the linear predictors of the link functions
joint.1z0

Jointly modelling of multiple variables taking values from [0,1) when there is a single random variable in the linear predictors of the link functions
fixed01

Fixed-effects beta regression with inflation at 0 and 1
zoib

Bayesian Inference for Zero/One Inflated Beta Regression
joint.2z01

Jointly modelling of multiple variables taking values from [0,1] when there are multiple random variables in the linear predictors of the link functions
sep.2z1

Separately modelling of multiple response variables taking values from (0,1] when there are multiple random variables in the linear predictors of the link functions
zoib-package

Bayesian Inference for Beta Regression and Zero-or-One-Inflated Beta Regression Models
joint.2z1

Jointly modelling of multiple variables taking values from (0,1] when there are multiple random variables in the linear predictors of the link functions
sep.1z

Separately modelling of multiple response variables taking values from (0,1) when there a single random variable in the linear predictors of the link functions
joint.2z

Jointly modelling of multiple variables taking values from (0,1) when there are multiple random variables in the linear predictors of the link functions
sep.1z01

Separately modelling of multiple response variables taking values from [0,1] when there a single random variable in the linear predictors of the link functions
sep.1z0

Separately modelling of multiple response variables taking values from [0,1) when there a single random variable in the linear predictors of the link functions
sep.1z1

Separately modelling of multiple response variables taking values from (0,1] when there a single random variable in the linear predictors of the link functions
sep.2z0

Separately modelling of multiple response variables taking values from [0,1) when there are multiple random variables in the linear predictors of the link functions
joint.2z0

Jointly modelling of multiple variables taking values from [0,1) when there are multiple random variables in the linear predictors of the link functions
fixed0

Fixed-effects beta regression model with inflation at 0
check.psrf

Convergence Check for Markov Chain Monte Carlo simulations via Potential Scale Reduction Factor
sep.2z

Separately modelling of multiple response variables taking values from (0,1) when there are multiple random variables in the linear predictors of the link functions
fixed1

Fixed-effects beta regression with inflation at 1
joint.1z

Jointly modeling of multiple variables taking values from (0,1) when there is a single random variable in the linear predictors of the link functions
fixed

Fixed-effects beta regression with no inflation at 0 or 1
AlcoholUse

California County-level Teenager Monthly Alcohol Use data
paraplot

visual display of the posterior inferences of the parameters from a zoib model
sep.2z01

Separately modelling of multiple response variables taking values from [0,1] when there are multiple random variables in the linear predictors of the link functions