Package: lsm
Type: Package
Title: Estimation of the log Likelihood of the Saturated Model
Version: 0.1.8
Date: 2018-08-30
Authors@R: c(person("Humberto", "Llinas", role = c("aut")),
  person("Omar", "Fabregas", role = c("aut")),
  person("Jorge", "Villalba", email = "jlvia1191@gmail.com", role = c("aut", "cre")))
Author: Humberto Llinas [aut],
  Omar Fabregas [aut],
  Jorge Villalba [aut, cre]
Maintainer: Jorge Villalba <jlvia1191@gmail.com>
Description: When the values of the outcome variable Y are either 0 or 1, the function lsm() calculates the estimation of the log likelihood in the saturated model. This model is characterized by Llinas (2006, ISSN:2389-8976) in section 2.3 through the assumptions 1 and 2. The function LogLik() works (almost perfectly) when the number of independent variables K is high, but for small K it calculates wrong values in some cases. For this reason, when Y is dichotomous and the data are grouped in J populations, it is recommended to use the function lsm() because it works very well for all K.
Depends: R (>= 3.1.0),stats
Encoding: UTF-8
URL: https://github.com/jlvia1191/lsm
License: MIT + file LICENSE
LazyData: TRUE
RoxygenNote: 6.1.0
Collate: 'lsm.R'
NeedsCompilation: no
Packaged: 2018-08-30 07:59:08 UTC; jorgeR
Repository: CRAN
Date/Publication: 2018-08-30 08:12:13 UTC
