Description Usage Arguments Details Author(s) References Examples
View source: R/BetaReg_family.R
BetaReg
implements a mboost
family object to boost beta regression.
1 |
mu |
starting value for location paramer. |
phirange |
range for the optimization of scale parameter phi. |
BetaReg
implements 'classical' beta regression for model-based boosting. Location parameter mu
is modeled by additive predictor, scale parameter phi is simultaneously optimized as a scalar and treated as nuisance.
Andreas Mayr <mayr@uni-bonn.de>
Mayr A, Weinhold L, Hofner B, Titze S, Gefeller O, Schmid M (2018). The betaboost package - a software tool for modeling bounded outcome variables in potentially high-dimensional data. International Journal of Epidemiology, doi: 10.1093/ije/dyy093.
Schmid M, Wickler F, Maloney KO, Mitchell R, Fenske N, & Mayr A. (2013). Boosted beta regression. PLoS ONE, 8(4), e61623.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | require(gamlss.dist)
# simple simulated example
set.seed(1234)
x1 <- rnorm(100)
x2 <- rnorm(100)
x3 <- rnorm(100)
x4 <- rnorm(100)
y <- rBE(n = 100, mu = plogis(x1 + x2),
sigma = plogis(x3 + x4))
data <- data.frame(y ,x1, x2, x3, x4)
data <- data[!data$y %in% c(0,1),]
# 'classic' beta regression
b1 <- betaboost(formula = y ~ x1 + x2, data = data,
iterations = 120)
coef(b1)
# compare to mboost
b2 <- glmboost(y ~ x1 + x2, data = data, family = BetaReg())
coef(b2)
# different values due to different defaults for step length and mstop
# same model with mboost
b3 <- glmboost(y ~ x1 + x2, data = data, family = BetaReg(),
control = boost_control(mstop = 120, nu = 0.01))
coef(b3)
coef(b1)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.