# Matthias Kohl

#### 22 packages on CRAN

#### 3 packages on Bioconductor

Contains several functions for statistical data analysis; e.g. for sample size and power calculations, computation of confidence intervals and tests, and generation of similarity matrices.

RFLPtools provides functions to analyse DNA fragment samples (i.e. derived from RFLP-analysis) and standalone BLAST report files (i.e. DNA sequence analysis).

Functions for the determination of optimally robust influence curves and estimators in case of normal location and/or scale.

Functions for the determination of optimally robust influence curves and estimators for preprocessing omics data, in particular gene expression data.

Functions for the determination of optimally robust influence curves in case of linear regression with unknown scale and standard normal distributed errors where the regressor is random.

Optimally robust estimation in general smoothly parameterized models using S4 classes and methods.

Optimally robust estimation using S4 classes and methods. Old version still needed for current versions of ROptRegTS and RobRex.

A collection of miscellaneous basic statistic functions and convenience wrappers for efficiently describing data. The author's intention was to create a toolbox, which facilitates the (notoriously time consuming) first descriptive tasks in data analysis, consisting of calculating descriptive statistics, drawing graphical summaries and reporting the results. The package contains furthermore functions to produce documents using MS Word (or PowerPoint) and functions to import data from Excel. Many of the included functions can be found scattered in other packages and other sources written partly by Titans of R. The reason for collecting them here, was primarily to have them consolidated in ONE instead of dozens of packages (which themselves might depend on other packages which are not needed at all), and to provide a common and consistent interface as far as function and arguments naming, NA handling, recycling rules etc. are concerned. Google style guides were used as naming rules (in absence of convincing alternatives). The 'camel style' was consequently applied to functions borrowed from contributed R packages as well.

An R6 object oriented distributions package. Unified interface for 42 probability distributions and 11 kernels including functionality for multiple scientific types. Additionally functionality for composite distributions and numerical imputation. Design patterns including wrappers and decorators are described in Gamma et al. (1994, ISBN:0-201-63361-2). For quick reference of probability distributions including d/p/q/r functions and results we refer to McLaughlin, M. P. (2001). Additionally Devroye (1986, ISBN:0-387-96305-7) for sampling the Dirichlet distribution, Gentle (2009) <doi:10.1007/978-0-387-98144-4> for sampling the Multivariate Normal distribution and Michael et al. (1976) <doi:10.2307/2683801> for sampling the Wald distribution.

Provides documentation in form of a common vignette to packages 'distr', 'distrEx', 'distrMod', 'distrSim', 'distrTEst', 'distrTeach', and 'distrEllipse'.

S4-classes for setting up a coherent framework for simulation within the distr family of packages.

Provides flexible examples of LLN and CLT for teaching purposes in secondary school.

Evaluation (S4-)classes based on package distr for evaluating procedures (estimators/tests) at data/simulation in a unified way.

Functions for calculating sample size and power for clinical trials with multiple (co-)primary endpoints.

Includes 'sysdata.rda' file for packages of the 'RobASt' - family of packages; is currently used by package 'RobExtremes' only.

Optimally robust estimation for extreme value distributions using S4 classes and methods (based on packages 'distr', 'distrEx', 'distrMod', 'RobAStBase', and 'ROptEst').

Functions for the selection of optimal reference genes and the normalisation of real-time quantitative PCR data.

The package provides functions to read raw RT-qPCR data of different platforms.