| gamlss-package {gamlss} | R Documentation |
Generalized Additive Models for Location Scale and Shape
Description
Functions for fitting the Generalized Additive Models for Location Scale and Shape introduced by Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The models use a distributional regression approach where all the parameters of the conditional distribution of the response variable are modelled using explanatory variables.
Details
The DESCRIPTION file:
| Package: | gamlss |
| Title: | Generalized Additive Models for Location Scale and Shape |
| Version: | 5.4-22 |
| Date: | 2024-03-18 |
| Authors@R: | c(person("Mikis", "Stasinopoulos", role = c("aut", "cre", "cph"), email = "d.stasinopoulos@gre.ac.uk", comment = c(ORCID = "0000-0003-2407-5704")), person("Robert", "Rigby", role = "aut", email = "r.rigby@gre.ac.uk", comment = c(ORCID = "0000-0003-3853-1707")), person("Vlasios", "Voudouris", role = "ctb"), person("Calliope", "Akantziliotou", role = "ctb"), person("Marco", "Enea", role = "ctb"), person("Daniil", "Kiose", role = "ctb", comment = c(ORCID = "0000-0002-3596-5748")), person("Achim", "Zeileis", role = "ctb", email = "Achim.Zeileis@R-project.org", comment = c(ORCID = "0000-0003-0918-3766")) ) |
| Description: | Functions for fitting the Generalized Additive Models for Location Scale and Shape introduced by Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The models use a distributional regression approach where all the parameters of the conditional distribution of the response variable are modelled using explanatory variables. |
| License: | GPL-2 | GPL-3 |
| URL: | https://www.gamlss.com/ |
| BugReports: | https://github.com/gamlss-dev/gamlss/issues |
| Depends: | R (>= 3.3.0), graphics, stats, splines, utils, grDevices, gamlss.data (>= 5.0-0), gamlss.dist (>= 4.3.1), nlme, parallel |
| Imports: | MASS, survival, methods |
| Suggests: | distributions3 (>= 0.2.1) |
| LazyLoad: | yes |
| NeedsCompilation: | yes |
| Author: | Mikis Stasinopoulos [aut, cre, cph] (<https://orcid.org/0000-0003-2407-5704>), Robert Rigby [aut] (<https://orcid.org/0000-0003-3853-1707>), Vlasios Voudouris [ctb], Calliope Akantziliotou [ctb], Marco Enea [ctb], Daniil Kiose [ctb] (<https://orcid.org/0000-0002-3596-5748>), Achim Zeileis [ctb] (<https://orcid.org/0000-0003-0918-3766>) |
| Maintainer: | Mikis Stasinopoulos <d.stasinopoulos@gre.ac.uk> |
Index of help topics:
.binom Lists used by GAMLSS
IC Gives the GAIC for a GAMLSS Object
LR.test Likelihood Ratio test for nested GAMLSS models
Q.stats A function to calculate the Q-statistics
Rsq Generalised (Pseudo) R-squared for GAMLSS
models
VC.test Vuong and Clarke tests
acfResid ACF plot of the residuals
additive.fit Implementing Backfitting in GAMLSS
bfp Functions to fit fractional polynomials in
GAMLSS
bp Bucket plot
calibration Calibrating centile curves
centiles Plots the centile curves for a GAMLSS object
centiles.com Comparing centiles from different GAMLSS models
centiles.pred Creating predictive centiles values
centiles.split Plots centile curves split by x for a GAMLSS
object
coef.gamlss Extract Model Coefficients in a GAMLSS fitted
model
cs Specify a Smoothing Cubic Spline Fit in a
GAMLSS Formula
deviance.gamlss Global Deviance of a GAMLSS model
devianceIncr The global deviance increment
dtop Detrended transformed Owen's plot
edf Effective degrees of freedom from gamlss model
find.hyper A function to select values of hyper-parameters
in a GAMLSS model
fitDist Fitting Different Parametric 'gamlss.family'
Distributions.
fitted.gamlss Extract Fitted Values For A GAMLSS Model
fittedPlot Plots The Fitted Values of a GAMLSS Model
formula.gamlss Extract the Model Formula in a GAMLSS fitted
model
gamlss Generalized Additive Models for Location Scale
and Shape
gamlss-package Generalized Additive Models for Location Scale
and Shape
gamlss.control Auxiliary for Controlling GAMLSS Fitting
gamlss.cs Support for Function cs() and scs()
gamlss.fp Support for Function fp()
gamlss.lo Support for Function lo()
gamlss.ps Support for Functions for smoothers
gamlss.random Support for Functions random() and re()
gamlss.scope Generate a Scope Argument for Stepwise GAMLSS
gamlssML Maximum Likelihood estimation of a simple
GAMLSS model
gamlssVGD A Set of Functions for selecting Models using
Validation or Test Data Sets and Cross
Validation
gen.likelihood A function to generate the likelihood function
from a GAMLSS object
getPEF Getting the partial effect function from a
continuous term in a GAMLSS model
getQuantile Getting the partial quantile function for a
term
getSmo Extracting Smoother information from a GAMLSS
fitted object
glim.control Auxiliary for Controlling the inner algorithm
in a GAMLSS Fitting
histDist This function plots the histogram and a fitted
(GAMLSS family) distribution to a variable
histSmo Density estimation using the Poisson trick
lms A function to fit LMS curves for centile
estimation
lo Specify a loess fit in a GAMLSS formula
loglogSurv Survival function plots for checking the tail
behaviour of the data
lpred Extract Linear Predictor Values and Standard
Errors For A GAMLSS Model
model.frame.gamlss Extract a model.frame, a model matrix or terms
from a GAMLSS object for a given distributional
parameter
numeric.deriv An internal GAMLSS function for numerical
derivatives
par.plot A function to plot parallel plot for repeated
measurement data
pcat Reduction for the Levels of a Factor.
pdf.plot Plots Probability Distribution Functions for
GAMLSS Family
plot.gamlss Plot Residual Diagnostics for an GAMLSS Object
plot.histSmo A Plotting Function for density estimator
object histSmo
plot2way Function to plot two interaction in a GAMLSS
model
polyS Auxiliary support for the GAMLSS
predict.gamlss Extract Predictor Values and Standard Errors
For New Data In a GAMLSS Model
print.gamlss Prints a GAMLSS fitted model
prodist.gamlss Extracting Fitted or Predicted Probability
Distributions from gamlss Models
prof.dev Plotting the Profile Deviance for one of the
Parameters in a GAMLSS model
prof.term Plotting the Profile: deviance or information
criterion for one of the terms (or
hyper-parameters) in a GAMLSS model
ps P-Splines Fits in a GAMLSS Formula
quantSheets Quantile Sheets
random Specify a random intercept model in a GAMLSS
formula
refit Refit a GAMLSS model
residuals.gamlss Extract Residuals from GAMLSS model
ri Specify ridge or lasso Regression within a
GAMLSS Formula
rqres.plot Creating and Plotting Randomized Quantile
Residuals
rvcov Robust Variance-Covariance matrix of the
parameters from a fitted GAMLSS model
stepGAIC Choose a model by GAIC in a Stepwise Algorithm
summary.gamlss Summarizes a GAMLSS fitted model
term.plot Plot regression terms for a specified parameter
of a fitted GAMLSS object
update.gamlss Update and Re-fit a GAMLSS Model
wp Worm plot
z.scores Z-scores for lms objects
Author(s)
Mikis Stasinopoulos [aut, cre, cph] (<https://orcid.org/0000-0003-2407-5704>), Robert Rigby [aut] (<https://orcid.org/0000-0003-3853-1707>), Vlasios Voudouris [ctb], Calliope Akantziliotou [ctb], Marco Enea [ctb], Daniil Kiose [ctb] (<https://orcid.org/0000-0002-3596-5748>), Achim Zeileis [ctb] (<https://orcid.org/0000-0003-0918-3766>)
Maintainer: Mikis Stasinopoulos <d.stasinopoulos@gre.ac.uk>
References
Nelder, J. A. and Wedderburn, R. W. M. (1972). Generalized linear models. J. R. Statist. Soc. A., 135 370-384.
Hastie, T. J. and Tibshirani, R. J. (1990). Generalized Additive Models. Chapman and Hall, London.
Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion), Appl. Statist., 54, part 3, pp 507-554.
Rigby, R. A., Stasinopoulos, D. M., Heller, G. Z., and De Bastiani, F. (2019) Distributions for modeling location, scale, and shape: Using GAMLSS in R, Chapman and Hall/CRC. An older version can be found in https://www.gamlss.com/.
Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, https://www.jstatsoft.org/v23/i07/.
Stasinopoulos D. M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017) Flexible Regression and Smoothing: Using GAMLSS in R, Chapman and Hall/CRC.
(see also https://www.gamlss.com/).
See Also
Examples
data(abdom)
mod<-gamlss(y~pb(x),sigma.fo=~pb(x),family=BCT, data=abdom, method=mixed(1,20))
plot(mod)
rm(mod)