Title: Hierarchical Multinomial Marginal Models
Imports: quadprog, MASS, mvtnorm, nleqslv

Package: hmmm
Version: 1.0.0
Date: 2012-10-26
Title: hierarchical multinomial marginal models
Author: Roberto Colombi, Sabrina Giordano, Manuela Cazzaro
Maintainer: Colombi Roberto <colombi@unibg.it>
Description: Functions for specifying and fitting marginal models for
contingency tables proposed by Bergsma and Rudas (2002) here
called hierarchical multinomial marginal models (hmmm) and
their extensions presented by Bartolucci et al.  (2007);
multinomial Poisson homogeneous (mph) models and homogeneous
linear predictor (hlp) models for contingency tables proposed
by Lang (2004) and (2005); hidden Markov models where the
distribution of the observed variables is described by a
marginal model.  Inequality constraints on the parameters are
allowed and can be tested.
Depends: quadprog, MASS
License: GPL (>= 2)
Packaged: 2012-11-17 16:24:19 UTC; Sabrina
Repository: CRAN
Date/Publication: 2012-11-17 19:41:32

Title: "Mixture and Hidden Markov Models with R" Datasets and Example
Description: Datasets and code examples that accompany our book Visser & Speekenbrink (2021), "Mixture and Hidden Markov Models with R", <https://depmix.github.io/hmmr/>.

Description: Implements an S3 class for storing and formatting time-of-day

person("The R Consortium", role = "cph")

Suggests: crayon, lubridate, pillar, testthat

person("The R Consortium", role = "fnd")
Suggests: crayon, lubridate, pillar (>= 1.1.0), testthat

person("The R Consortium", role = "fnd"),
Imports: methods, pkgconfig, rlang, vctrs (>= 0.2.0)

Imports: methods, pkgconfig, rlang, vctrs (>= 0.2.1)

Imports: ellipsis, lifecycle, methods, pkgconfig, rlang, vctrs (>=
Suggests: crayon, lubridate, pillar (>= 1.1.0), testthat (>= 3.0.0)

Imports: ellipsis (>= 0.3.2), lifecycle, methods, pkgconfig, rlang,

person("Kirill", "Müller", role = c("aut", "cre"), email = "kirill@cynkra.com", comment = c(ORCID = "0000-0002-1416-3412")),

Tracks elapsed clock time using a hms() scalar
(inherits from difftime() with seconds as the unit).