ais {FMsmsnReg}

Australian institute of sport data

Description

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

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

##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)