Imports: bootstrap, graphics, MASS, stats

Authors@R: person("Sangchul", "Park", email = "mail@sangchul.com", role = c("aut", "cre"))
Description: Wipe out tags in a html document and extract a text from it.
Packaged: 2017-09-04 04:26:38 UTC; Sangchul Park

Description: Convert a html document to a simple plain text by removing all html tags.
Packaged: 2017-10-14 21:15:00 UTC; Sangchul Park

Description: Convert a html document to simple plain texts by removing all html tags.  This package utilizes regular expressions to strip off html tags. It also offers gettxt() and browse() function, which enables you to get or browse texts at a certain web page.
Packaged: 2017-10-18 16:02:15 UTC; Sangchul Park

Packaged: 2017-10-18 21:22:31 UTC; Sangchul Park

Description: Convert a html document to plain texts by stripping off all html tags.

Package: htmcglm
Type: Package
Title: Hypothesis Testing for McGLMs
Version: 0.0.1
Author: Lineu Alberto Cavazani de Freitas [aut, cre],
Wagner Hugo Bonat [ctb],
Walmes Marques Zeviani [ctb]
Maintainer: Lineu Alberto Cavazani de Freitas <lineuacf@gmail.com>
Authors@R: c(person(c("Lineu Alberto","Cavazani"), "de Freitas", role = c("aut", "cre"),
email = "lineuacf@gmail.com"),
person(c("Wagner","Hugo"), "Bonat", role = "ctb"),
person(c("Walmes", "Marques"), "Zeviani", role = "ctb"))
Description: Performs hypothesis testing for multivariate covariance generalized linear
models (McGLMs).  McGLM is a general framework for non-normal
multivariate data analysis, designed to handle multivariate response
variables, along with a wide range of temporal and spatial correlation
structures defined in terms of a covariance link function combined
with a matrix linear predictor involving known matrices.
The models take non-normality into account in the conventional way
by means of a variance function, and the mean structure is modelled
by means of a link function and a linear predictor.
The models are fitted using an efficient Newton scoring algorithm
based on quasi-likelihood and Pearson estimating functions, using
only second-moment assumptions. This provides a unified approach to
a wide variety of different types of response variables and covariance
structures, including multivariate extensions of repeated measures,
time series, longitudinal, spatial and spatio-temporal structures.
The package offers a user-friendly interface for fitting McGLMs
similar to the glm() R function.
License: MIT + file LICENSE
URL: https://github.com/lineu96/htmcglm
Encoding: UTF-8
RoxygenNote: 7.2.0
Imports: stats, doBy, Matrix, mcglm, sjmisc, stringr
NeedsCompilation: no
Packaged: 2022-07-20 20:13:15 UTC; lacf14
Repository: CRAN
Date/Publication: 2022-07-21 12:10:06 UTC