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

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

## Documentation for package ‘bamlss’ version 1.1-7

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

A B C D E F G H I J L M N O P Q R S T V W Z

bamlss-package | Bayesian Additive Models for Location Scale and Shape (and Beyond)

## -- A --

ALD_bamlss | Distribution Families in 'bamlss'
AR1 | AR1 Transformer Function
AR1_bamlss | Distribution Families in 'bamlss'
Austria | Austria States and Topography
AustriaTopo | Austria States and Topography

## -- B --

bamlss | Fit Bayesian Additive Models for Location Scale and Shape (and Beyond)
bamlss.engine.helpers | BAMLSS Engine Helper Functions
bamlss.engine.setup | BAMLSS Engine Setup Function
bamlss.family | Distribution Families in 'bamlss'
bamlss.formula | Formulae for BAMLSS
bamlss.frame | Create a Model Frame for BAMLSS
bamlss.model.frame | BAMLSS Model Frame
BayesX | Markov Chain Monte Carlo for BAMLSS using 'BayesX'
BayesX.control | Markov Chain Monte Carlo for BAMLSS using 'BayesX'
bayesx2 | Some Shortcuts
bbfit | Batchwise Backfitting
bbfitp | Batchwise Backfitting
bboost | Bootstrap Boosting
bboost_plot | Bootstrap Boosting
beta1_bamlss | Distribution Families in 'bamlss'
beta_bamlss | Distribution Families in 'bamlss'
bfit | Fit BAMLSS with Backfitting
bfit_glmnet | Fit BAMLSS with Backfitting
bfit_iwls | Fit BAMLSS with Backfitting
bfit_iwls_lm | Fit BAMLSS with Backfitting
bfit_iwls_Matrix | Fit BAMLSS with Backfitting
bfit_iwls_optim | Fit BAMLSS with Backfitting
bfit_lm | Fit BAMLSS with Backfitting
bfit_optim | Fit BAMLSS with Backfitting
binomial_bamlss | Distribution Families in 'bamlss'
boost | Boosting BAMLSS
boost2 | Some Shortcuts
boostm | Boosting BAMLSS
boost_frame | Boosting BAMLSS
boost_plot | Boosting BAMLSS
boost_summary | Boosting BAMLSS
BUGSeta | Markov Chain Monte Carlo for BAMLSS using JAGS
BUGSmodel | Markov Chain Monte Carlo for BAMLSS using JAGS

## -- C --

c95 | Compute 95% Credible Interval and Mean
cnorm_bamlss | Distribution Families in 'bamlss'
coef.bamlss | Extract BAMLSS Coefficients
colorlegend | Plot a Color Legend
confint.bamlss | Extract BAMLSS Coefficients
continue | Continue Sampling
contribplot | Batchwise Backfitting
cox_bamlss | Distribution Families in 'bamlss'
cox_mcmc | Cox Model Markov Chain Monte Carlo
cox_mode | Cox Model Posterior Mode Estimation
cox_predict | Cox Model Prediction
Crazy | Crazy simulated data
CRPS | Continuous Rank Probability Score

## -- D --

DIC | Deviance Information Criterion
dirichlet_bamlss | Distribution Families in 'bamlss'
dl.bamlss | Deep Learning BAMLSS
dw_bamlss | Distribution Families in 'bamlss'

## -- E --

ELF_bamlss | Distribution Families in 'bamlss'
engines | Show Available Engines for a Family Object

## -- F --

family.bamlss | Distribution Families in 'bamlss'
family.bamlss.frame | Distribution Families in 'bamlss'
fatalities | Weekly Number of Fatalities in Austria
fitted.bamlss | BAMLSS Fitted Values

## -- G --

GAMart | GAM Artificial Data Set
gamlss_distributions | Extract Distribution families of the 'gamlss.dist' Package
gamma_bamlss | Distribution Families in 'bamlss'
gaussian2_bamlss | Distribution Families in 'bamlss'
Gaussian_bamlss | Distribution Families in 'bamlss'
gaussian_bamlss | Distribution Families in 'bamlss'
GEFCom2014 | GEFCom2014 Electricity Load Data
get.par | BAMLSS Engine Helper Functions
get.state | BAMLSS Engine Helper Functions
get_BayesXsrc | Markov Chain Monte Carlo for BAMLSS using 'BayesX'
GEV_bamlss | Distribution Families in 'bamlss'
gF | Get a BAMLSS Family
glogis_bamlss | Distribution Families in 'bamlss'
GMCMC | General Markov Chain Monte Carlo for BAMLSS
GMCMC_iwls | General Markov Chain Monte Carlo for BAMLSS
GMCMC_iwlsC | General Markov Chain Monte Carlo for BAMLSS
GMCMC_iwlsC_gp | General Markov Chain Monte Carlo for BAMLSS
GMCMC_slice | General Markov Chain Monte Carlo for BAMLSS
Golf | Prices of Used Cars Data
gpareto_bamlss | Distribution Families in 'bamlss'
gumbel_bamlss | Distribution Families in 'bamlss'

## -- H --

homstart_data | HOMSTART Precipitation Data

## -- I --

isgd | Implicit Stochastic Gradient Descent Optimizer

## -- J --

JAGS | Markov Chain Monte Carlo for BAMLSS using JAGS
jm_bamlss | Fit Flexible Additive Joint Models
jm_mcmc | Fit Flexible Additive Joint Models
jm_mode | Fit Flexible Additive Joint Models
jm_predict | Fit Flexible Additive Joint Models
jm_survplot | Fit Flexible Additive Joint Models
jm_transform | Fit Flexible Additive Joint Models

## -- L --

la | Lasso Smooth Constructor
lasso | Lasso Smooth Constructor
lasso2 | Some Shortcuts
lasso_coef | Lasso Smooth Constructor
lasso_plot | Lasso Smooth Constructor
lasso_stop | Lasso Smooth Constructor
lasso_transform | Lasso Smooth Constructor
lin | Linear Effects for BAMLSS
logNN_bamlss | Distribution Families in 'bamlss'
lognormal_bamlss | Distribution Families in 'bamlss'
LondonBoroughs | London Fire Data
LondonBoundaries | London Fire Data
LondonFire | London Fire Data
LondonFStations | London Fire Data

## -- M --

make_weights | Neural Networks for BAMLSS
mix_bamlss | Distribution Families in 'bamlss'
model.frame.bamlss | BAMLSS Model Frame
model.frame.bamlss.frame | BAMLSS Model Frame
model.matrix.bamlss.formula | Construct/Extract BAMLSS Design Matrices
model.matrix.bamlss.frame | Construct/Extract BAMLSS Design Matrices
model.matrix.bamlss.terms | Construct/Extract BAMLSS Design Matrices
multinomial_bamlss | Distribution Families in 'bamlss'
MVNORM | Create Samples for BAMLSS by Multivariate Normal Approximation
mvnormAR1_bamlss | Distribution Families in 'bamlss'
mvnorm_bamlss | Distribution Families in 'bamlss'

## -- N --

n | Neural Networks for BAMLSS
n.weights | Neural Networks for BAMLSS
nbinom_bamlss | Distribution Families in 'bamlss'
neighbormatrix | Compute a Neighborhood Matrix from Spatial Polygons

## -- O --

opt_bbfit | Batchwise Backfitting
opt_bbfitp | Batchwise Backfitting
opt_bfit | Fit BAMLSS with Backfitting
opt_boost | Boosting BAMLSS
opt_boostm | Boosting BAMLSS
opt_Cox | Cox Model Posterior Mode Estimation
opt_isgd | Implicit Stochastic Gradient Descent Optimizer
opt_JM | Fit Flexible Additive Joint Models
opt_lasso | Lasso Smooth Constructor

## -- P --

parameters | Extract or Initialize Parameters for BAMLSS
pathplot | Plot Coefficients Paths
plot.bamlss | Plotting BAMLSS
plot.bamlss.residuals | Compute BAMLSS Residuals
plot.bamlss.results | Plotting BAMLSS
plot.boost_summary | Boosting BAMLSS
plot.stabsel | Stability selection.
plot2d | Plot 2D Effects
plot3d | Plot 3D Effects
plotblock | Factor Variable and Random Effects Plots
plotmap | Plot Maps
plotneighbors | Compute a Neighborhood Matrix from Spatial Polygons
plotnonp | Plot 2D Effects
poisson_bamlss | Distribution Families in 'bamlss'
predict.bamlss | BAMLSS Prediction
predict.bboost | Bootstrap Boosting
predict.dl.bamlss | Deep Learning BAMLSS
Predict.matrix.kriging.smooth | Kriging Smooth Constructor
Predict.matrix.tensorX.smooth | Markov Chain Monte Carlo for BAMLSS using 'BayesX'
Predict.matrix.tensorX3.smooth | Markov Chain Monte Carlo for BAMLSS using 'BayesX'
predictn | Neural Networks for BAMLSS
print.boost_summary | Boosting BAMLSS
print.summary.bamlss | Summary for BAMLSS

## -- Q --

quant_bamlss | Markov Chain Monte Carlo for BAMLSS using 'BayesX'

## -- R --

randomize | Transform Smooth Constructs to Random Effects
rb | Random Bits for BAMLSS
residuals.bamlss | Compute BAMLSS Residuals
response_name | Extract the reponse name of a 'bamlss.frame' object.
results.bamlss.default | Compute BAMLSS Results for Plotting and Summaries
rJM | Simulate longitudinal and survival data for joint models
rmf | Remove Special Characters
rSurvTime2 | Simulate Survival Times

## -- S --

s2 | Special Smooths in BAMLSS Formulae
samples | Extract Samples
samples.bamlss | Extract Samples
samples.bamlss.frame | Extract Samples
samplestats | Sampling Statistics
sam_BayesX | Markov Chain Monte Carlo for BAMLSS using 'BayesX'
sam_Cox | Cox Model Markov Chain Monte Carlo
sam_GMCMC | General Markov Chain Monte Carlo for BAMLSS
sam_JAGS | Markov Chain Monte Carlo for BAMLSS using JAGS
sam_JM | Fit Flexible Additive Joint Models
sam_MVNORM | Create Samples for BAMLSS by Multivariate Normal Approximation
scale2 | Scaling Vectors and Matrices
set.par | BAMLSS Engine Helper Functions
set.starting.values | BAMLSS Engine Helper Functions
Sichel_bamlss | Distribution Families in 'bamlss'
simJM | Simulate longitudinal and survival data for joint models
simSurv | Simulate Survival Times
sliceplot | Plot Slices of Bivariate Functions
smooth.construct | Constructor Functions for Smooth Terms in BAMLSS
smooth.construct.bamlss.formula | Constructor Functions for Smooth Terms in BAMLSS
smooth.construct.bamlss.frame | Constructor Functions for Smooth Terms in BAMLSS
smooth.construct.bamlss.terms | Constructor Functions for Smooth Terms in BAMLSS
smooth.construct.kr.smooth.spec | Kriging Smooth Constructor
smooth.construct.linear.smooth.spec | Linear Effects for BAMLSS
smooth.construct.ms.smooth.spec | Smooth constructor for monotonic P-splines
smooth.construct.randombits.smooth.spec | Random Bits for BAMLSS
smooth.construct.sr.smooth.spec | Random Effects P-Spline
smooth.construct.tensorX.smooth.spec | Markov Chain Monte Carlo for BAMLSS using 'BayesX'
smooth.construct.tensorX3.smooth.spec | Markov Chain Monte Carlo for BAMLSS using 'BayesX'
smooth_check | MCMC Based Simple Significance Check for Smooth Terms
stabsel | Stability selection.
summary.bamlss | Summary for BAMLSS
Surv2 | Create a Survival Object for Joint Models
surv_transform | Survival Model Transformer Function
sx | Markov Chain Monte Carlo for BAMLSS using 'BayesX'

## -- T --

terms.bamlss | BAMLSS Model Terms
terms.bamlss.formula | BAMLSS Model Terms
terms.bamlss.frame | BAMLSS Model Terms
trans_AR1 | AR1 Transformer Function
trans_random | Transform Smooth Constructs to Random Effects
tx | Markov Chain Monte Carlo for BAMLSS using 'BayesX'
tx2 | Markov Chain Monte Carlo for BAMLSS using 'BayesX'
tx3 | Markov Chain Monte Carlo for BAMLSS using 'BayesX'
tx4 | Markov Chain Monte Carlo for BAMLSS using 'BayesX'

## -- V --

Volcano | Artificial Data Set based on Auckland's Maunga Whau Volcano

## -- W --

WAIC | Watanabe-Akaike Information Criterion (WAIC)
weibull_bamlss | Distribution Families in 'bamlss'

## -- Z --

ztnbinom_bamlss | Distribution Families in 'bamlss'