InfMort {gamlss.data}

Infant Mortality Data

Description

The following data set is not real data set but it is created for the purpose of demonstrating a binomial type response variable. The data set is based on some real data obtained from the Parana State in Brazil in 2010.

Usage

data("InfMort")

Format

A data frame with 399 observations on the following 11 variables.

x

the x-coordinate

y

the y-coordinate

dead

the number of dead infants

bornalive

the number of infants born alive

IFDM

FIRJAN index of city development

illit

the illiteracy index

lGDP

the logarithm of the gross national product

cli

the proportion of children living in a household with half the basic salary

lpop

the logarithm of the number of people living in each city

PSF

the proportion covered by the family health program

poor

the proportion of individuals low household income per capita

Details

There is geographical information given by the x and y coordidates and also several social-economics variables.

References

Rigby, R. A. and Stasinopoulos D. M.(2005). Generalized additive models for location, scale and shape, (with discussion),Appl. Statist., 54, part 3, pp 507-554.

Rigby, R. A., Stasinopoulos, D. M., Heller, G. Z., and De Bastiani, F. (2019) Distributions for modeling location, scale, and shape: Using GAMLSS in R, Chapman and Hall/CRC. An older version can be found in https://www.gamlss.com/.

Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, doi:10.18637/jss.v023.i07.

Stasinopoulos D. M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017) Flexible Regression and Smoothing: Using GAMLSS in R, Chapman and Hall/CRC.

(see also https://www.gamlss.com/).

Examples

data(InfMort)