RBesT

Ankylosing Spondylitis.

Exact Confidence interval for Binary Proportion

Functional programming utilities

R Bayesian Evidence Synthesis Tools

Summarize Arrays

Automatic Fitting of Mixtures of Conjugate Distributions to a Sample

Scrambles the order of a mcmc array object for usage as a mcmc sample. It is advisable to set order once per mcmc run, otherwise correlations in the mcmc sample will be lost.

Fast column-wise calculation of unbiased variances

Ulcerative Colitis.

Crohn's disease.

Beta-Binomial Probabilities

Decision Function for 1 Sample Designs

Decision Boundary for 1 Sample Designs

Decision Function for 2 Sample Designs

Decision Boundary for 2 Sample Designs

Transform Densities with a link function

Effective Sample Size for a Conjugate Prior

Fill numeric objects

Forest Plot

Meta-Analytic-Predictive Analysis for Generalized Linear Models

internal function used for integration of densities which appears to be much more stable from -Inf to +Inf in the logit space while the density to be integrated recieves inputs from 0 to 1 such that the inverse distribution function must be used. The integral solved is int_x dmix(mix,x) integrand(x) where integrand must be given as log and we integrate over the support of mix.

k nearest neighbor algorithm for multi-variate data

Read and Set Likelihood to the Corresponding Conjugate Prior

Logit (log-odds) and inverse-logit function.

Extract log likelihood from fitted EM objects

Matrix version of log_sum_exp

Numerically stable log of the inv_logit function

Numerically stable summation of logs

Mixture Distributions

Beta Mixture Density

Combine Mixture Distributions

Difference of mixture distributions

Utility function to instantiate 2 parameter mixture densities.

Fit of Mixture Densities to Samples

The Gamma Mixture Distribution

takes x and transforms it according to the defined link function of the mixture

Normal Mixture Density

Operating Characteristics for 1 Sample Design

Operating Characteristics for 2 Sample Design

Diagnostic plots for EM fits

Diagnostic plots for gMAP analyses

Plot mixture distributions

Probability of Success for a 1 Sample Design

Probability of Success for 2 Sample Design

Conjugate Posterior Analysis

Predictive Distributions for Mixture Distributions

Predictions from gMAP analyses

Robustify Mixture Priors

Support of Distributions

Transplant.

Find root of univariate function of integers