Mikkel Meyer Andersen and Poul Svante Eriksen
Discrete Laplace Family for models such as a generalized
linear model

Discrete Laplace exponential family for models such as a
generalized linear model

The discrete Laplace exponential family for use in fitting generalized linear models.

Discrete Laplace exponential family for models such as a generalized linear model

Discrete Laplace mixture inference using the EM algorithm
disclapmix makes inference in a mixture of Discrete
Laplace distributions using the EM algorithm.
R (>= 2.14.0), disclap, cluster, parallel

disclapmix makes inference in a mixture of Discrete Laplace distributions using the EM algorithm. This can e.g. be used for modelling the distribution of Y chromosomal haplotypes as described in [1, 2] (refer to the URL section).

ggplot2, gridExtra, ggdendro, scales, seriation

Discrete Laplace Mixture Inference using the EM Algorithm
Make inference in a mixture of discrete Laplace distributions using the EM algorithm. This can e.g. be used for modelling the distribution of Y chromosomal haplotypes as described in [1, 2] (refer to the URL section).

Rcpp (>= 0.11), disclap (>= 1.4), cluster (>= 1.14.4), stats,
graphics, methods, utils

c(
person(given = "Mikkel Meyer", family = "Andersen",
email = "mikl@math.aau.dk", role = c("aut", "cre")),
person(given = "Poul Svante", family = "Eriksen",
email = "svante@math.aau.dk", role = c("aut"))
)
Mikkel Meyer Andersen [aut, cre],
Poul Svante Eriksen [aut]
Rcpp (>= 0.11), disclap (>= 1.4), cluster (>= 1.14.4), MASS,
stats, graphics, methods, utils
knitr, ggplot2, gridExtra, ggdendro, scales, seriation,
fwsim, testthat, rmarkdown

knitr, ggplot2, gridExtra, ggdendro, scales, seriation,
fwsim, testthat

Test for Discretized Normality in Ordinal Data
Tests whether multivariate ordinal data may stem from discretizing a multivariate normal distribution.
The test is described by Foldnes and Grønneberg (2019) <doi:10.1080/10705511.2019.1673168>.
lavaan, arules, sirt, MASS, pbivnorm, psych

Tests whether multivariate ordinal data may stem from discretizing a multivariate normal distribution.
The test is described by Foldnes and Grønneberg (2019) <doi:10.1080/10705511.2019.1673168>.
In addition, an adjusted polychoric correlation estimator is provided that takes marginal knowledge into account,
as described by Grønneberg and Foldnes (2022) <doi:10.1037/met0000495>.
lavaan (>= 0.6.10), arules, sirt, MASS, pbivnorm, cubature,
copula, mnormt, GoFKernel