Description Format References Examples
Data on 102 male and 100 female athletes collected at the Australian Institute of Sport.
This data frame contains the following columns:
(0 = male or 1 = female)
height (cm)
weight (kg)
lean body mass
red cell count
white cell count
Hematocrit
Hemoglobin
plasma ferritin concentration
body mass index, weight/height^2
sum of skin folds
Percent body fat
Case Labels
Sport
S. Weisberg (2005). Applied Linear Regression, 3rd edition. New York: Wiley, Section 6.4
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | ##Load the data
library(FMsmsnReg)
data(ais)
attach(ais)
#Set the response y and covariate x
x1 <- cbind(1,SSF,Ht)
y <- Bfat
##Fits a linear Regression Model with Finite Mixtures of Skew t
parST <- FMsmsnReg(y, x1, g=2, get.init = TRUE, criteria = TRUE,
group = FALSE,family = "Skew.t", error = 10^-4,
iter.max = 2000,obs.prob= FALSE, kmeans.param = NULL,show.converge=FALSE,cp=0.5)
##Fits a linear Regression Models with Finite Mixtures of Skew normal
parSN <- FMsmsnReg(y, x1, g=2, get.init = TRUE, criteria = TRUE,
group = FALSE,family = "Skew.normal", error = 10^-4,
iter.max = 5000,obs.prob= FALSE, kmeans.param = NULL,show.converge=FALSE,cp=0.5)
##Fits a linear Regression Models with Finite Mixtures of Skew Contaminated Normal
parCN <- FMsmsnReg(y, x1, g=2, get.init = TRUE, criteria = TRUE,
group = FALSE,family = "Skew.cn", error = 10^-4,
iter.max = 5000,obs.prob= FALSE, kmeans.param = NULL,show.converge=FALSE,cp=0.5)
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