## Recently Published

##### Frequentist vs Noninformative Bayesian inference in the Binomial model

Frequentist vs Noninformative Bayesian inference in the Binomial model using Uniform and Jeffreys priors.

##### Visual comparison of two populations

Some visual tools for comparing two univariate samples

##### Flexible linear mixed models: HIV-1 viral load after unstructured treatment interruption

A real data example of linear mixed models for censored responses with flexible random effects and flexible residual errors.

##### Flexible linear mixed models: Framingham study

A real data application of linear mixed models with flexible errors and flexible random effects.

##### How to create a random Secret Santa list in R

Two different methods to create a Secret Santa random list in R from a list of names.

##### An Introduction to MCMC

Illustration of some properties of MCMC samplers

##### Predictive Beta Binomial distribution

The predictive distribution for a Binomial sampling model with Beta prior.

##### The Normal-Normal Bayesian model (known variance)

The posterior distribution of the mean for a normal sampling model with known variance and normal prior distribution

##### The Beta-Binomial model

A short description of the Binomial distribution, the Beta distribution, and the Bayesian Beta-Binomial model.

##### The Inverse Mills Ratio

Some properties of the Inverse Mills Ratio

##### Kernel Density and Distribution Estimation for data with different supports

R codes to implement kernel density and distribution estimators for data with support on R, R_+, and (0,1) by using a transformation approach.

##### Bayesian Variable Selection: Analysis of DLD data

Tractable Bayesian Variable Selection: Beyond normality. Analysis of DLD data using two-piece residual errors and non-local priors.

##### The Generalised Weibull Distribution

Cumulative distribution function, quantile function, hazard function, and cumulative hazard function of the Generalised Weibull distribution.

##### The Exponentiated Weibull distribution

Probability density function, cumulative distribution function, quantile function, random number generation, hazard function, and cumulative hazard function of the Exponentiated Weibull distribution.

##### An objective prior for the number of degrees of freedom of a multivariate t distribution

An objective prior for the number of degrees of freedom of a multivariate t distribution

##### The Jeffreys prior for skew–symmetric models

The Jeffreys prior for the skewness parameter in skew–symmetric models

##### Kullback Leibler divergence between a multivariate t and a multivariate normal distributions

A tractable, scalable, expression for the Kullback Leibler divergence between a multivariate t and a multivariate normal distributions

##### Kullback Leibler divergence between two multivariate t distributions

A tractable, scalable, expression for the Kullback Leibler divergence between two multivariate t distributions

##### An application of an objective prior for the number of degrees of freedom of a multivariate t distribution

A financial application of an objective prior for the number of degrees of freedom of a multivariate t distribution

##### Nonparametric estimation of P(X<Y) for paired data

Several types of Nonparametric estimators of P(X<Y) for paired data

##### Galton’s Forecasting Competition

Galton’s Forecasting Competition data modelling using the DTP R package.

##### A weakly informative prior for the degrees of freedom of the t distribution

Implementation of a weakly informative prior for the degrees of freedom of the t distribution.

##### Mollified two-piece distributions

Mollification of two-piece distributions.

##### The Laplace and two-piece Laplace Distributions

Implementation of the Laplace and two piece Laplace distributions (using the R package twopiece).

##### Natural (non-) informative priors for the skew-normal distribution

Real data example to illustrate the use of Jeffreys and Total Variation priors for the shape parameter of the skew-normal distribution

##### t-copula with t and two piece t marginals

A real data example to illustrate how to fit a t-copula with t and two piece t marginals

##### TPSAS R Package

The TPSAS R package implements the univariate two-piece sinh–arcsinh distribution

##### Sinh-arcsinh distribution

Implementation of the probability density function, cumulative distribution function, quantile function, and random number generation of the SAS distribution.

##### Bayesian inference for the ratio of the means of two normals

Bayesian inference for the ratio of the means of two normal populations with unequal variances using reference priors.

##### Approximate Maximum Likelihood Estimation (AMLE)

A simple approach to maximum intractable likelihood estimation: AMLE. Two toy examples.

##### Ratio of two normals and a normal approximation

Implementaion of the distribution of the ratio of two independent normal distributions and a normal approximation.

##### Posterior QQ envelopes: normality test

Implementation of Posterior QQ envelopes for normality test.

##### Posterior QQ envelopes: Linear regression

Implementation of Posterior QQ envelopes and predictive QQ plots in the context of linear regression.

##### Flexible AFT Models III: Bayesian + two-piece

Bayesian AFT models with two-piece errors

##### Flexible AFT Models II: Bayesian + skew-symmetric

Bayesian Accelerated Failure Time models with skew-symmetric errors.

##### Flexible AFT Models I: MLE + two-piece

Accelerated failure time models with two-piece errors using maximum likelihood estimation.

##### twopiece R package with applications

The twopiece R package implements the family of Two-Piece distributions.

##### DTP R package

The DTP R package implements the family of Double Two-Piece distributions.

##### Two-piece Generalised Hyperbolic distribution

Description and implementation of the two-piece Generalised Hyperbolic distribution.

##### Two-piece Variance Gamma distribution

Implementation and description of the two-piece Variance Gamma distribution.

##### Two-piece Johnson-SU distribution

Implementation and description of the two-piece Johnson-SU distribution