InfMort: Infant Mortality Data
In gamlss.data: Data for Generalised Additive Models for Location Scale and Shape

InfMort

R Documentation

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, \Sexpr[results=rd]{tools:::Rd_expr_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/).