Title: Multivariate Sparse Group Lasso for the Multivariate Multiple
Linear Regression with an Arbitrary Group Structure
Author: Yanming Li <liyanmin@umich.edu>, Bin Nan <bnan@umich.edu>, Ji Zhu <jizhu@umich.edu>
Description: For fitting multivariate response and multiple predictor linear regressions with an arbitrary group structure assigned on the regression coefficient matrix, using the multivariate sparse group lasso and the mixed coordinate descent algorithm.

Title: Assess Tumor Microsatellite Instability with a Decision Tree
Description: A decision tree classifier for detecting microsatellite instability (MSI) in somatic mutation data from whole exome sequencing. MSI is detected based on different mutation rates in all sites as well as in simple sequence repeats. This mechanism can also be applied to sequence data of targeted gene panels with shorter sequence length.
Depends: IRanges, RWeka, rJava, R.utils, R (>= 3.1.0)
Packaged: 2014-08-29 07:03:52 UTC; minihuang

Depends: IRanges, RWeka, rJava, R.utils, R (>= 3.2.0)
Packaged: 2015-06-15 12:10:59 UTC; minihuang

Title: Multivariate Statistical Methods with R Applications
Description: Data sets in the book entitled "Multivariate Statistical Methods with R Applications", H.Bulut (2018).
The book will be published in Turkish and the original name of this book be "R Uygulamalari ile Cok Degiskenli Istatistiksel Yontemler".

The book will be published in Turkish and the original name of this book will be "R Uygulamalari ile Cok Degiskenli Istatistiksel Yontemler".

The book was published in Turkish and the original name of this book will be "R Uygulamalari ile Cok Degiskenli Istatistiksel Yontemler".

Package: MSPRT
Type: Package
Title: Modified Sequential Probability Ratio Test (MSPRT)
Version: 1.0
Date: 2018-09-11
Authors@R: c(person("Sandipan", "Pramanik", email = "sandy@stat.tamu.edu",
role = c("aut", "cre")),
person("Valen E.", "Johnson", role = "aut"),
person("Anirban", "Bhattacharya", role = "aut") )
Author: Sandipan Pramanik [aut, cre],
Valen E. Johnson [aut],
Anirban Bhattacharya [aut]
Maintainer: Sandipan Pramanik <sandy@stat.tamu.edu>
Description: A modified SPRT (MSPRT) can be designed and implemented with the help of this package. In a
MSPRT design, the maximum sample size of an experiment is fixed prior to the start of an
experiment, the alternative hypothesis used to define the rejection region of the test is
derived from the size of the test (Type I error), the maximum available sample size (N), and
the targeted Type 2 error (equal to 1 minus the power) is also prespecified. Given these values,
the MSPRT is defined in a manner very similar to Wald's initial proposal. This test can reduce
the average sample size required to perform statistical hypothesis tests at the specified levels
of significance and power. This package facilitates the carrying out of one sample Z tests, T Tests
and tests of binomial success probabilities. A user guidance for this software package is provided
here and also in the supplemental information.
Imports: nleqslv, ggplot2, foreach, iterators, parallel, doParallel,
datasets, graphics, grDevices, methods, stats, utils
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-09-11 16:56:52 UTC; sandipanpramanik
Repository: CRAN
Date/Publication: 2018-09-17 14:50:03 UTC