Suggests: texreg (>= 1.37.1), testthat, knitr, rmarkdown, ggplot2
Packaged: 2020-06-17 08:24:23 UTC; tobias.ruettenauer

Packaged: 2021-01-05 21:26:06 UTC; tobias.ruettenauer

Packaged: 2021-01-11 00:07:28 UTC; tobias.ruettenauer

Packaged: 2021-01-15 11:13:35 UTC; tobias.ruettenauer

Packaged: 2021-02-24 15:45:50 UTC; tobias.ruettenauer

Imports: Formula, plm, Rdpack, stats, dplyr
Packaged: 2022-04-01 13:52:28 UTC; tobias.ruettenauer

Description: A small package for determining if n-dimensional ellipses overlap.

Title: Functional Help for Functions, Objects, and Packages
Provides pseudo-postfix operators and more to enhance displaying documents.
The `?.` pseudo-postfix operator and the `?` prefix operator displays documents and contents (source or structure) of objects simultaneously to help understanding the objects.
The `?p` pseudo-postfix operator displays package documents, and is shorter than help(package = foo).
Suggests: knitr, pkgdown, printr, rmarkdown, roxygen2, testthat (>=

Suggests: knitr, pkgdown, printr, roxygen2, testthat (>= 2.1.0), covr

Suggests: knitr, printr, testthat (>= 2.1.0), covr, rmarkdown

Enhance R help system by fuzzy search and preview interface, pseudo-postfix operators, and more.
Imports: prettycode, curl, data.table, dplyr, htmltools, magrittr,
matrixStats, miniUI, reactable, rstudioapi, rlang, shiny,

Title: Output analysis of FEMME model results
Author: Henrik Andersson, Andreas Hofmann, Karline Soetaert
Description: Plot and summarize results calculated by the modeling environment FEMME (Soetaert, 2002)
Packaged: Tue Feb 28 09:35:22 2006; hornik

Packaged: Mon Feb 23 10:48:03 2009; hornik

Title: Using Fence Methods for Model Selection
Author: Jiming Jiang, Jianyang Zhao, J. Sunil Rao, Thuan Nguyen
Description: This method is a new class of model selection strategies,
for mixed model selection, which includes linear and generalized linear
mixed models. The idea involves a procedure to isolate a subgroup of what
are known as correct models (of which the optimal model is a member). This is
accomplished by constructing a statistical fence, or barrier, to carefully
eliminate incorrect models. Once the fence is constructed, the optimal model is
selected from among those within the fence according to a criterion which can
1. Jiang J., Rao J.S., Gu Z., Nguyen T. (2008),  Fence Methods for Mixed Model Selection.
The Annals of Statistics, 36(4): 1669-1692.
2. Jiang J., Nguyen T., Rao J.S. (2009), A Simplified Adaptive Fence Procedure.
Statistics and Probability Letters, 79, 625-629.
3. Jiang J., Nguyen T., Rao J.S. (2010), Fence Method for Nonparametric Small Area Estimation.
4. Jiming Jiang, Thuan Nguyen and J. Sunil Rao (2011), Invisible fence methods and the identification of differentially expressed gene sets.
Statistics and Its Interface, Volume 4, 403-415.
5. Thuan Nguyen & Jiming Jiang (2012), Restricted fence method for covariate selection in longitudinal data analysis.
6. Thuan Nguyen, Jie Peng, Jiming Jiang (2014), Fence Methods for Backcross Experiments.
Statistical Computation and Simulation, 84(3), 644-662.
7. Jiang, J. (2014), The fence methods, in Advances in Statistics, Hindawi Publishing Corp., Cairo.
8. Jiming Jiang and Thuan Nguyen (2015), The Fence Methods, World Scientific, Singapore.
Imports: MASS, stats, lme4, ggplot2, compiler, sae, fields, grDevices,