Description: This entry-level toolkit allows performing generic continuous-time microsimulation for a wide range of demograhic applications.

Description: This entry-level toolkit allows performing continuous-time microsimulation for a wide range of demographic applications. Individual life-courses are specified by a continuous-time multi-state model.

Description: The package performs continuous-time microsimulations for population projections.

Description: This entry-level toolkit allows performing continuous-time microsimulation for a wide range of life science (demography, social sciences, epidemiology) applications. Individual life-courses are specified by a continuous-time multi-state model.

Title: Utilities for Official Spanish Microdata
Authors@R: c( person("Carlos J.", "Gil Bellosta", email="cgb@datanalytics.com", role=c('aut', 'cre')),
person("José Luis", "Cañadas Reche", email = "canadasreche@gmail.com", role="ctb"))
Description: The MicroDatosEs package provides utilities for reading and processing microdata from Spanish official statistics with R
Author: Carlos J. Gil Bellosta [aut, cre],

person("Carlos", "Neira", email = "cneirac@gmail.com", role="ctb"),

person("Diego", "Paniagua Sánchez", email = "dpansan@gmail.com", role="ctb"),
Description: The MicroDatosEs package provides utilities for reading and processing microdata from Spanish official statistics with R.

Description: Provides utilities for reading and processing microdata from Spanish official statistics with R.

person("Fiorella", "Mori Peláez", email = "fiorella.mori.pelaez@gmail.com", role="ctb"),
person("Jorge", "López Pérez", email = "jorge@loperez.com", role="ctb"),
person("Estitxu", "Villamor", email = "estitxu.villamor@ehu.eus", role="ctb"),

Description: Most multilevel methodologies can only model macro-micro
multilevel situations in an unbiased way, wherein group-level predictors
(e.g., city temperature) are used to predict an individual-level
outcome variable (e.g., citizen personality). In contrast,
this R package enables researchers to model micro-macro situations, wherein
individual-level (micro) predictors (and other group-level predictors) are
used to predict a group-level (macro) outcome variable in an unbiased way.
Authors@R: c(person(c("Jackson", "G"),"Lu", email= "jackson.guannan.lu@gmail.com", role="aut"),
person(c("Nancy", "R"),"Xu", email= "nancyranxu@gmail.com", role=c("aut", "cre")))
Packaged: 2017-07-01 13:50:00 UTC; JacksonLuOld
Maintainer: Nancy R Xu <nancyranxu@gmail.com>