Learn R Programming

⚠️There's a newer version (1.2-5) of this package.Take me there.

bamlss (version 1.2-3)

Bayesian Additive Models for Location, Scale, and Shape (and Beyond)

Description

Infrastructure for estimating probabilistic distributional regression models in a Bayesian framework. The distribution parameters may capture location, scale, shape, etc. and every parameter may depend on complex additive terms (fixed, random, smooth, spatial, etc.) similar to a generalized additive model. The conceptual and computational framework is introduced in Umlauf, Klein, Zeileis (2019) and the R package in Umlauf, Klein, Simon, Zeileis (2021) .

Copy Link

Version

Install

install.packages('bamlss')

Monthly Downloads

1,143

Version

1.2-3

License

GPL-2 | GPL-3

Maintainer

Nikolaus Umlauf

Last Published

March 18th, 2024

Functions in bamlss (1.2-3)

Prices of Used Cars Data

General Markov Chain Monte Carlo for BAMLSS

Continuous Rank Probability Score

Temperature data.

London Fire Data

Formulae for BAMLSS

Markov Chain Monte Carlo for BAMLSS using JAGS

bamlss.engine.setup

BAMLSS Engine Setup Function

Create a Survival Object for Joint Models

Create Samples for BAMLSS by Multivariate Normal Approximation

Markov Chain Monte Carlo for BAMLSS using BayesX

Artificial Data Set based on Auckland's Maunga Whau Volcano

AR1 Transformer Function

GAM Artificial Data Set

Deviance Information Criterion

Crazy simulated data

Watanabe-Akaike Information Criterion (WAIC)

Compute 95% Credible Interval and Mean

Continue Sampling

Batchwise Backfitting

Bayesian Additive Models for Location Scale and Shape (and Beyond)

Create a Model Frame for BAMLSS

Plot a Color Legend

Boosting BAMLSS

Cox Model Markov Chain Monte Carlo

Fit Bayesian Additive Models for Location Scale and Shape (and Beyond)

Extract BAMLSS Coefficients

bamlss.engine.helpers

BAMLSS Engine Helper Functions

Fit BAMLSS with Backfitting

Bootstrap Boosting

Get a BAMLSS Family

Cholesky MVN (disttree)

Deep Distributional Neural Network

Cox Model Prediction

Cox Model Posterior Mode Estimation

gamlss_distributions

Extract Distribution families of the gamlss.dist Package

Weekly Number of Fatalities in Austria

BAMLSS Fitted Values

Distribution Families in bamlss

Show Available Engines for a Family Object

Lasso Smooth Constructor

Formula Generator

HOMSTART Precipitation Data

Implicit Stochastic Gradient Descent Optimizer

Fit Flexible Additive Joint Models

smooth.construct.kr.smooth.spec

Kriging Smooth Constructor

model.frame.bamlss

BAMLSS Model Frame

Linear Effects for BAMLSS

Modified Cholesky MVN

model.matrix.bamlss.frame

Construct/Extract BAMLSS Design Matrices

Neural Networks for BAMLSS

Compute a Neighborhood Matrix from Spatial Polygons

Extract or Initialize Parameters for BAMLSS

Plot 3D Effects

Plotting BAMLSS

Factor Variable and Random Effects Plots

results.bamlss.default

Compute BAMLSS Results for Plotting and Summaries

Plot Coefficients Paths

Extract the reponse name of a bamlss.frame object.

Special Smooths in BAMLSS Formulae

Extract Samples

residuals.bamlss

Compute BAMLSS Residuals

Remove Special Characters

Plot 2D Effects

Transform Smooth Constructs to Random Effects

Plot Slices of Bivariate Functions

BAMLSS Prediction

Scaling Vectors and Matrices

Reference data.

Sampling Statistics

Simulate Survival Times

smooth.construct.sr.smooth.spec

Random Effects P-Spline

Create distributions3 Object

smooth.construct

Constructor Functions for Smooth Terms in BAMLSS

smooth.construct.ms.smooth.spec

Smooth constructor for monotonic P-splines

BAMLSS Model Terms

MCMC Based Simple Significance Check for Smooth Terms

Random Bits for BAMLSS

Stability selection.

Simulate longitudinal and survival data for joint models

Survival Model Transformer Function

Summary for BAMLSS