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FMsmsnReg (version 1.0)

ais: Australian institute of sport data

Description

Data on 102 male and 100 female athletes collected at the Australian Institute of Sport.

Arguments

Format

This data frame contains the following columns:
Sex
(0 = male or 1 = female)
Ht
height (cm)
Wt
weight (kg)
LBM
lean body mass
RCC
red cell count
WCC
white cell count
Hc
Hematocrit
Hg
Hemoglobin
Ferr
plasma ferritin concentration
BMI
body mass index, weight/height^2
SSF
sum of skin folds
Bfat
Percent body fat
Label
Case Labels
Sport
Sport

References

S. Weisberg (2005). Applied Linear Regression, 3rd edition. New York: Wiley, Section 6.4

Examples

Run this code

##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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