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.
xthe x-coordinate
ythe y-coordinate
deadthe number of dead infants
bornalivethe number of infants born alive
IFDMFIRJAN index of city development
illitthe illiteracy index
lGDPthe logarithm of the gross national product
clithe proportion of children living in a household with half the basic salary
lpopthe logarithm of the number of people living in each city
PSFthe proportion covered by the family health program
poorthe 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/).