bmi {mixsmsn}

Body Mass Index

Description

The data set has the measure of the Body Mass Index (bmi) for 2107 people.

Usage

data(bmi)

Format

A data frame with 2107 observations of bmi

Source

Rodrigo M. Basso, Victor H. Lachos, Celso R. B. Cabral, Pulak Ghosh (2009). "Robust mixture modeling based on scale mixtures of skew-normal distributions". Computational Statistics and Data Analysis (in press). doi: 10.1016/j.csda.2009.09.031

References

Marcos Oliveira Prates, Celso Romulo Barbosa Cabral, Victor Hugo Lachos (2013)."mixsmsn: Fitting Finite Mixture of Scale Mixture of Skew-Normal Distributions". Journal of Statistical Software, 54(12), 1-20., URL https://doi.org/10.18637/jss.v054.i12.

Examples

## Not run: 
data(bmi)
y <-bmi$bmi

hist(y,breaks=40)

## Maximum likelihood estimaton (MLE) with generated values
bmi.analysis <- smsn.mix(y, nu = 3, g = 2, get.init = TRUE, criteria = TRUE, 
                         group = TRUE, calc.im=TRUE)
mix.hist(y,bmi.analysis)

## Passing initial values to MLE
mu1 <- 20; mu2 <- 35
sigma2.1 <- 9; sigma2.2 <- 9;
lambda1 <- 0; lambda2 <- 0;
pii<- c(0.5,0.5)

mu <- c(mu1,mu2)
sigma2 <- c(sigma2.1,sigma2.2)
shape <- c(lambda1,lambda2)

bmi.analysis <- smsn.mix(y, nu = 3, mu, sigma2 , shape, pii, get.init = FALSE,
                         criteria = TRUE, group = TRUE, calc.im=FALSE)
mix.hist(y,bmi.analysis)

## Calculate the information matrix (when the calc.im option in smsn.mix is set FALSE)
bmi.im <-  im.smsn(y, bmi.analysis)

## Search for the best number of clusters from g=1 to g=5
bmi.analysis <- smsn.search(y, nu = 3, g.min = 1, g.max=5)
mix.hist(y,bmi.analysis$best.model)

## End(Not run)