Packaged: 2011-10-14 16:39:49 UTC; troutinthemilk

Depends: fgui, tools, runjags, coda, lattice, ellipse, plotrix,
Packaged: 2012-02-19 15:48:03 UTC; troutinthemilk

Packaged: 2012-05-19 15:38:23 UTC; troutinthemilk

Packaged: 2012-06-01 15:05:14 UTC; troutinthemilk

Packaged: 2012-09-14 13:46:22 UTC; troutinthemilk

Packaged: 2012-11-18 21:26:30 UTC; troutinthemilk

Packaged: 2012-12-03 17:12:46 UTC; troutinthemilk

Description: Estimates diet contributions from isotopic sources using JAGS.
Includes estimation of concentration dependence and measurement error.

Imports: fgui, runjags, colorspace, ellipse, plotrix
Packaged: 2015-11-10 15:47:09 UTC; jakeferguson

Packaged: 2016-01-07 18:55:36 UTC; troutinthemilk

Packaged: 2016-06-15 15:39:52 UTC; troutinthemilk

Title: IR-Tree Modeling in 'mirt', 'Mplus', or 'TAM'
Authors@R: person("Hansjörg", "Plieninger", email = "mail@hansjoerg.me",
Description: Item response tree (IR-tree) models are a class of item response
theory (IRT) models that assume that the responses to polytomous items can
best be explained by multiple psychological processes; see Böckenholt
'ItemResponseTrees' allows to fit such IR-tree models in 'mirt', 'Mplus', or
'TAM'. The package automates some of the hassle of IR-tree modeling by means
of a consistent syntax. This allows new users to quickly adopt this model
class, and this allows experienced users to fit many complex models
Imports: backports, checkmate (>= 1.9), dplyr, generics, glue,
magrittr, MASS, Matrix, methods, mirt (>= 1.30), purrr, rlang
(>= 0.4.0), sets, stringr, tibble, tidyr (>= 1.0.0), tidyselect
Suggests: covr, future, knitr, listenv, lme4, modeltests (>= 0.1.0),
MplusAutomation (>= 0.7), progress, rmarkdown, roxygen2,
simsalapar, sfsmisc, spelling, TAM, testthat (>= 2.1.0)

Imports: checkmate (>= 1.9), dplyr, generics, glue, magrittr, MASS,
Matrix, methods, mirt (>= 1.30), purrr, rlang (>= 0.4.0), sets,
stringr, tibble, tidyr (>= 1.0.0), tidyselect
simsalapar, sfsmisc, spelling, TAM (>= 3.5-19), testthat (>=

Title: Iterative Hard Thresholding Extensions to Cyclops
person("Patrick", "Ryan", role = "aut"),
person("Observational Health Data Sciences and Informatics", role = "cph")
Description: Fits large-scale regression models with a penalty that
restricts the maximum number of non-zero regression coefficients
to a prespecified value.  While Chu et al (2020) <doi:10.1093/gigascience/giaa044>
describe the basic algorithm, this package uses Cyclops for an efficient implementation.
Observational Health Data Sciences and Informatics [cph]