Title: An Implementation of Common Response Time Trimming Methods
Description: Provides various commonly-used response time trimming
methods, including the recursive / moving-criterion methods reported by
Van Selst and Jolicoeur (1994). By passing trimming functions raw data files,
the package will return trimmed data ready for inferential testing.
Author: James Grange [aut, cre]
Maintainer: James Grange <grange.jim@gmail.com>
Diff between trimr versions 1.0.0 dated 2015-08-02 and 1.0.1 dated 2015-08-28
DESCRIPTION | 6 - MD5 | 20 ++-- R/datasets.R | 2 R/modifiedRecursive.R | 16 ++- README.md | 34 +++++-- data/linearInterpolation.rda |binary inst/doc/trimr-vignette.R | 40 ++++++++ inst/doc/trimr-vignette.Rmd | 68 ++++++++++++++ inst/doc/trimr-vignette.html | 203 ++++++++++++++++++++++++++++++------------- man/linearInterpolation.Rd | 2 vignettes/trimr-vignette.Rmd | 68 ++++++++++++++ 11 files changed, 377 insertions(+), 82 deletions(-)
Title: Analysis of Kin-Cohort Studies
Description: Analysis of kin-cohort studies. kin.cohort provides estimates of age-specific
cumulative risk of a disease for carriers and noncarriers of a mutation. The cohorts are
retrospectively built from relatives of probands for whom the genotype is known. Currently
the method of moments and marginal maximum likelihood are implemented. Confidence intervals
are calculated from bootstrap samples.
Most of the code is a translation from previous 'MATLAB' code by N. Chatterjee.
Author: Victor Moreno, Nilanjan Chatterjee, Bhramar Mukherjee
Maintainer: Victor Moreno <v.moreno@iconcologia.net>
Diff between kin.cohort versions 0.6 dated 2009-01-29 and 0.7 dated 2015-08-28
DESCRIPTION | 35 ++++---- MD5 |only NAMESPACE | 19 ++-- inst/ChangeLog | 7 + man/kc.marginal.Rd | 118 +++++++++++++-------------- man/kc.moments.Rd | 110 +++++++++++++------------ man/kin.cohort.Rd | 146 +++++++++++++++++---------------- man/simulations.Rd | 228 ++++++++++++++++++++++++++--------------------------- 8 files changed, 341 insertions(+), 322 deletions(-)
Title: Modified Variance Estimators for Generalized Estimating
Equations
Description: Generalized estimating equations with the original sandwich variance estimator proposed by Liang and Zeger (1986), and eight types of more recent modified variance estimators for improving the finite small-sample performance.
Author: Ming Wang <mwang@phs.psu.edu>
Maintainer: Zheng Li <zheng.li@outlook.com>
Diff between geesmv versions 1.1 dated 2015-05-29 and 1.2 dated 2015-08-28
DESCRIPTION | 10 - MD5 | 8 - NAMESPACE | 1 R/GEE.var.fg.R | 294 ++++++++++++++++++++++++++++----------------------------- R/GEE.var.kc.R | 2 5 files changed, 158 insertions(+), 157 deletions(-)
Title: Nonparametric Multiple Expectile Regression via ER-Boost
Description: Expectile regression is a nice tool for estimating the conditional expectiles of a response variable given a set of covariates. This package implements a regression tree based gradient boosting estimator for nonparametric multiple expectile regression.
Author: Yi Yang <yiyang@umn.edu>, Hui Zou <hzou@stat.umn.edu>
Maintainer: Yi Yang <yiyang@umn.edu>
Diff between erboost versions 1.2 dated 2013-10-28 and 1.3 dated 2015-08-28
ChangeLog | 3 +++ DESCRIPTION | 13 +++++-------- MD5 | 18 +++++++++--------- NAMESPACE | 14 ++++++++++++++ R/erboost.R | 10 +++++----- man/erboost.Rd | 30 ++++++++++++++++++------------ man/erboost.perf.Rd | 8 ++------ man/plot.erboost.Rd | 6 +++--- man/relative.influence.Rd | 8 ++++---- man/summary.erboost.Rd | 8 ++++---- 10 files changed, 67 insertions(+), 51 deletions(-)
Title: Circle Manhattan Plot
Description: Manhattan plot, a type of scatter plot, was widely used to display the association results. However, it is usually time-consuming and laborious for a
non-specialist user to write scripts and adjust parameters of an elaborate plot. Moreover, the ever-growing traits measured have necessitated the
integration of results from different Genome-wide association study researches. Circle Manhattan Plot is the first open R package that can lay out
Genome-wide association study P-value results in both traditional rectangular patterns and novel circular ones. United in only one bull's eye style
plot, association results from multiple traits can be compared interactively, thereby to reveal both similarities and differences between signals.
Author: LiLin-Yin
Maintainer: LiLin-Yin <ylilin@163.com>
Diff between CMplot versions 2.0.1 dated 2015-06-16 and 3.0.1 dated 2015-08-28
DESCRIPTION | 10 +- MD5 | 8 - NAMESPACE | 2 R/CMplot.r | 204 +++++++++++++++++++++++++++++++++++--------------- man/CMplot-package.Rd | 65 ++++++++++++--- 5 files changed, 206 insertions(+), 83 deletions(-)