Description Usage Arguments Value Author(s) References Examples
A normal plot with simulated envelope of the residual is produced.
1 2 |
model |
object of class |
k |
number of replications for envelope construction. Default is 19. |
alpha |
value giving the size of the envelope. Default is 0.05 which is equivalent to a 95% band. |
res |
type of residuals to be extracted. Default is deviance. |
precision |
If |
dist |
The function RBS() defines the RBS distribution. |
A simulated envelope of the class RBS.
Manoel Santos-Neto manoel.ferreira@ufcg.edu.br, F.J.A. Cysneiros cysneiros@de.ufpe.br, Victor Leiva victorleivasanchez@gmail.com and Michelli Barros michelli.karinne@gmail.com
Atkinson, A. C. (1985) Plots, transformations and regression : an introduction to graphical methods of diagnostic regression analysis. Oxford Science Publications, Oxford.
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 30 31 | ## Fixed Precision
library(faraway)
data(cpd)
attach(cpd)
model0 = gamlss(actual ~ projected, family=RBS(mu.link="identity"),method=CG())
summary(model0)
set.seed(2015)
envelope(model0)
model = gamlss(actual ~ 0+projected, family=RBS(mu.link="identity"),method=CG())
summary(model)
set.seed(2015)
envelope(model)
##
library(alr3)
data(landrent)
attach(landrent)
resp <- I(Y/X1)
y1 <- split(resp, X4)$"1"
x21 <- split(X2, X4)$"1"
##Fixed Precision
fit0 <- gamlss(y1 ~ x21, family=RBS(mu.link="identity"),method=CG() )
summary(fit0)
set.seed(2015)
envelope(fit0,alpha=0.01, precision="fixed",res="quantile",dist=RBS(mu.link="identity"))
##Varying Precision
fit1 <- gamlss(y1 ~ x21,sigma.formula = y1 ~x21, family=RBS(mu.link="identity",sigma.link="sqrt"),method=CG() )
summary(fit11)
set.seed(2015)
envelope(fit1,alpha=0.01, precision="varying",res="quantile",dist=RBS(mu.link="identity",sigma.link="sqrt"))
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