person(given = "Sandra", family = "Siegfried", role = "aut",
Author: Sandra Siegfried [aut] (<https://orcid.org/0000-0002-7312-1001>),

person(given = "Luisa", family = "Barbanti", role = "aut",
The package also contains an experimental implementation of
multivariate count transformation models with an application
Imports: variables (>= 1.0-2), basefun (>= 1.0-5), alabama, Matrix,
Suggests: TH.data, knitr, lattice, colorspace, multcomp, mvtnorm,

person(given = "Sandra", family = "Siegfried", role = c("aut", "cre"),
person(given = "Torsten", family = "Hothorn", role = "aut",
to multi-species distribution models <arXiv:2201.13095>.
Packaged: 2022-07-06 13:28:24 UTC; siegfried
Author: Sandra Siegfried [aut, cre] (<https://orcid.org/0000-0002-7312-1001>),

Packaged: 2022-07-14 07:50:43 UTC; siegfried

Title: Consistant Cotrend Rank Selection
Maintainer: A. Christian Silva <a.christian.silva@gmail.com>
Description: Implements cointegration/cotrending rank selection
algorithm in Guo and Shintani (2013) "Consistant
cotrending rank selection when both stochastic and nonlinear
Numbered examples correspond to Feb 2011 preprint

Title: Consistent Co-Trending Rank Selection
Description: Implements cointegration/co-trending rank selection
algorithm in Guo and Shintani (2013) "Consistent
co-trending rank selection when both stochastic and nonlinear

algorithm in Guo and Shintani(2011). Paper: "Consistant
Cotrending rank selection when both stochastic and nonlinear
deterministic trends are present", Preprint, Feb 2011.

Title: Connect and work with couchDB databases
Depends: R (>= 3.0.0), RCurl, bitops, httr, rjson
SystemRequirements: couchDB instance to connect to and work on.

Title: Connect to and Work with CouchDB Databases
Description: Interface to the couchDB document database <http://couchdb.apache.org>.
SystemRequirements: couchDB instance to connect to and work with.

Title: Penalized Estimation of Flexible Hidden Markov Models for Time
Description: Provides tools for penalized estimation of flexible hidden Markov models for time series of counts w/o the need to specify a (parametric) family of distributions. These include functions for model fitting, model checking, and state decoding. For details, see Adam, T., Langrock, R., and Weiß, C.H. (2019): Penalized Estimation of Flexible Hidden Markov Models for Time Series of Counts. <arXiv:1901.03275>.