Automatic Fitting of Mixtures of Conjugate Distributions to a Sample
Effective Sample Size for a Conjugate Prior
Beta-Binomial Probabilities
Decision Function for 2 Sample Designs
Transform Densities with a link function
Forest Plot
Fill numeric objects
Decision Boundary for 2 Sample Designs
Decision Boundary for 1 Sample Designs
Decision Function for 1 Sample Designs
Meta-Analytic-Predictive Analysis for Generalized Linear Models
Numerically stable summation of logs
Logit (log-odds) and inverse-logit function.
Read and Set Likelihood to the Corresponding Conjugate Prior
Extract log likelihood from fitted EM objects
takes x and transforms it according to the defined link function of
the mixture
Matrix version of log_sum_exp
Normal Mixture Density
Diagnostic plots for gMAP analyses
Combine Mixture Distributions
Diagnostic plots for EM fits
Beta Mixture Density
Fit of Mixture Densities to Samples
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.
Predictive Distributions for Mixture Distributions
Robustify Mixture Priors
Mixture Distributions
Support of Distributions
Plot mixture distributions
The Gamma Mixture Distribution
Probability of Success for a 1 Sample Design
Find root of univariate function of integers
Transplant.
Predictions from gMAP analyses
Operating Characteristics for 2 Sample Design
Operating Characteristics for 1 Sample Design
k nearest neighbor algorithm for multi-variate data
Difference of mixture distributions
Probability of Success for 2 Sample Design
Utility function to instantiate 2 parameter mixture densities.
Conjugate Posterior Analysis
Ulcerative Colitis.
Ankylosing Spondylitis.
Fast column-wise calculation of unbiased variances
Summarize Arrays
Crohn's disease.
R Bayesian Evidence Synthesis Tools
Functional programming utilities
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.
Exact Confidence interval for Binary Proportion