Packaged: 2019-03-18 16:27:37 UTC; arthurtavares

Package: appell
Maintainer: Daniel Sabanes Bove <daniel.sabanesbove@ifspm.uzh.ch>
License: GPL (>= 3)
Title: Compute Appell's F1 hypergeometric function
LazyLoad: yes
Author: Daniel Sabanes Bove <daniel.sabanesbove@ifspm.uzh.ch> with
contributions by F. D. Colavecchia, R. C. Forrey, G. Gasaneo,
N. L. J. Michel, L. F.  Shampine, M. V. Stoitsov and H. A.
Watts.
Description: This package wraps Fortran code by F. D. Colavecchia and
G. Gasaneo for computing the Appell's F1 hypergeometric
function. Their program uses Fortran code by L. F. Shampine and
H. A. Watts. Moreover, the hypergeometric function with complex
arguments is computed with Fortran code by N. L. J. Michel and
M. V. Stoitsov or with Fortran code by R. C.  Forrey. See the
function documentations for the references and please cite them
accordingly.
Version: 0.0-3
Date: 2012-04-20
Depends: R (>= 2.14.0)
Collate: 'appellf1.R' 'appell-package.R' 'hyp2f1.R'
Packaged: 2012-04-20 14:55:22 UTC; daniel
Repository: CRAN
Date/Publication: 2012-04-20 15:41:31

Title: Approximate Path for Penalized Likelihood Estimators
Description: Approximate Path for Penalized Likelihood Estimators for Generalized Linear Models penalized by LASSO or MCP

Description: Approximate Path for Penalized Likelihood Estimators for
Generalized Linear Models penalized by LASSO or MCP

Title: Get Apple Search Ads Data via the 'Windsor.ai' API
Description: Collect  your data on digital marketing campaigns from Apple Search Ads using the 'Windsor.ai' API <https://windsor.ai/api-fields/>.

Title: 'Apple App Store' and 'iTunes' Data Extraction
Authors@R: person("Ashley", "Baldry", email = "arbaldry91@gmail.com", role = c("aut", "cre"))
Description: Using 'Apple App Store' <https://www.apple.com/app-store/> web scraping and 'iTunes' API
to extract content information, app ratings and reviews.
Imports: httr, jsonlite, rvest, glue, xml2, lubridate

Imports: httr, jsonlite, rvest, glue, xml2

Title: A Compilation of Applicability Domain Methods
person(given = "Marly", family = "Gotti", email = "marlygotti@gmail.com", role = c("aut", "cre")),
person(given = "Max", family = "Kuhn", email = "max@rstudio.com", role = c("aut")),
Description: A modeling package compiling applicability domain methods in R.
It combines different methods to measure the amount of extrapolation new
samples can have from the training set. See Netzeva et al (2005)
<doi:10.1177/026119290503300209> for an overview of applicability domains.
Imports: hardhat (>= 0.1.2), rlang, stats, glue, tibble, proxyC,
Matrix, dplyr, utils, purrr, tidyselect, tidyr
Suggests: recipes (>= 0.1.7), testthat (>= 2.1.0), knitr, rmarkdown,
covr, AmesHousing, spelling, xml2, modeldata
Packaged: 2020-06-15 02:42:20 UTC; marlygotti