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.

`data("InfMort")`

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

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

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, 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/).