Showing 3 of total 3 results (show query)
cran
mgcv:Mixed GAM Computation Vehicle with Automatic Smoothness Estimation
Generalized additive (mixed) models, some of their extensions and other generalized ridge regression with multiple smoothing parameter estimation by (Restricted) Marginal Likelihood, Generalized Cross Validation and similar, or using iterated nested Laplace approximation for fully Bayesian inference. See Wood (2017) <doi:10.1201/9781315370279> for an overview. Includes a gam() function, a wide variety of smoothers, 'JAGS' support and distributions beyond the exponential family.
Maintained by Simon Wood. Last updated 1 years ago.
32 stars 12.71 score 17k scripts 7.8k dependents
nicholasjclark
mvgam:Multivariate (Dynamic) Generalized Additive Models
Fit Bayesian Dynamic Generalized Additive Models to multivariate observations. Users can build nonlinear State-Space models that can incorporate semiparametric effects in observation and process components, using a wide range of observation families. Estimation is performed using Markov Chain Monte Carlo with Hamiltonian Monte Carlo in the software 'Stan'. References: Clark & Wells (2023) <doi:10.1111/2041-210X.13974>.
Maintained by Nicholas J Clark. Last updated 17 hours ago.
bayesian-statisticsdynamic-factor-modelsecological-modellingforecastinggaussian-processgeneralised-additive-modelsgeneralized-additive-modelsjoint-species-distribution-modellingmultilevel-modelsmultivariate-timeseriesstantime-series-analysistimeseriesvector-autoregressionvectorautoregressioncpp
148 stars 9.92 score 117 scriptscran
CUB:A Class of Mixture Models for Ordinal Data
For ordinal rating data, estimate and test models within the family of CUB models and their extensions (where CUB stands for Combination of a discrete Uniform and a shifted Binomial distributions); Simulation routines, plotting facilities and fitting measures are also provided.
Maintained by Rosaria Simone. Last updated 1 years ago.
3.48 score 1 dependents