mniw - The Matrix-Normal Inverse-Wishart Distribution
Density evaluation and random number generation for the Matrix-Normal Inverse-Wishart (MNIW) distribution, as well as the the Matrix-Normal, Matrix-T, Wishart, and Inverse-Wishart distributions. Core calculations are implemented in a portable (header-only) C++ library, with matrix manipulations using the 'Eigen' library for linear algebra. Also provided is a Gibbs sampler for Bayesian inference on a random-effects model with multivariate normal observations.
Last updated 2 months ago
6.16 score 4 stars 4 packages 30 scripts 325 downloadsSuperGauss - Superfast Likelihood Inference for Stationary Gaussian Time Series
Likelihood evaluations for stationary Gaussian time series are typically obtained via the Durbin-Levinson algorithm, which scales as O(n^2) in the number of time series observations. This package provides a "superfast" O(n log^2 n) algorithm written in C++, crossing over with Durbin-Levinson around n = 300. Efficient implementations of the score and Hessian functions are also provided, leading to superfast versions of inference algorithms such as Newton-Raphson and Hamiltonian Monte Carlo. The C++ code provides a Toeplitz matrix class packaged as a header-only library, to simplify low-level usage in other packages and outside of R.
Last updated 2 months ago
5.30 score 2 stars 2 packages 33 scripts 229 downloadsrdoxygen - Create Doxygen Documentation for Source Code
Create 'doxygen' documentation for source code in R packages, and optionally make it accessible as an R vignette. Includes a 'RStudio' Addin to easily trigger the doxygenize process.
Last updated 5 years ago
doxygenrcpprstudio-addin
4.93 score 17 stars 6 scripts 132 downloadsmsde - Bayesian Inference for Multivariate Stochastic Differential Equations
Implements an MCMC sampler for the posterior distribution of arbitrary time-homogeneous multivariate stochastic differential equation (SDE) models with possibly latent components. The package provides a simple entry point to integrate user-defined models directly with the sampler's C++ code, and parallelizes large portions of the calculations when compiled with 'OpenMP'.
Last updated 3 years ago
4.91 score 27 scripts 185 downloadsLocalCop - Local Likelihood Inference for Conditional Copula Models
Implements a local likelihood estimator for the dependence parameter in bivariate conditional copula models. Copula family and local likelihood bandwidth parameters are selected by leave-one-out cross-validation. The models are implemented in 'TMB', meaning that the local score function is efficiently calculated via automated differentiation (AD), such that quasi-Newton algorithms may be used for parameter estimation.
Last updated 2 months ago
4.85 score 1 stars 9 scripts 187 downloadsoptimCheck - Graphical and Numerical Checks for Mode-Finding Routines
Tools for checking that the output of an optimization algorithm is indeed at a local mode of the objective function. This is accomplished graphically by calculating all one-dimensional "projection plots" of the objective function, i.e., varying each input variable one at a time with all other elements of the potential solution being fixed. The numerical values in these plots can be readily extracted for the purpose of automated and systematic unit-testing of optimization routines.
Last updated 3 months ago
3.70 score 1 stars 1 scripts 174 downloadsMADPop - MHC Allele-Based Differencing Between Populations
Tools for the analysis of population differences using the Major Histocompatibility Complex (MHC) genotypes of samples having a variable number of alleles (1-4) recorded for each individual. A hierarchical Dirichlet-Multinomial model on the genotype counts is used to pool small samples from multiple populations for pairwise tests of equality. Bayesian inference is implemented via the 'rstan' package. Bootstrapped and posterior p-values are provided for chi-squared and likelihood ratio tests of equal genotype probabilities.
Last updated 9 months ago
3.70 score 1 stars 8 scripts 235 downloadsLMN - Inference for Linear Models with Nuisance Parameters
Efficient Frequentist profiling and Bayesian marginalization of parameters for which the conditional likelihood is that of a multivariate linear regression model. Arbitrary inter-observation error correlations are supported, with optimized calculations provided for independent-heteroskedastic and stationary dependence structures.
Last updated 3 years ago
3.70 score 1 stars 8 scripts 248 downloads