Detect Subgroup with an Enhanced Treatment Effect

A test for the existence of a subgroup with enhanced treatment effect. And, a sample size calculation procedure for the subgroup detection test.

Coordinated Networks Detection on Social Media

Detects a variety of coordinated actions on social media and outputs the network of coordinated users along with related information.

Multiple Testing of Local Extrema for Detection of Change Points

Simultaneously detect the number and locations of change points in piecewise linear models under stationary Gaussian noise allowing autocorrelated random noise. The core idea is to transform the problem of detecting change points into the detection of local extrema (local maxima and local minima)through kernel smoothing and differentiation of the data sequence, see Cheng et al. (2020) . A low-computational and fast algorithm call 'dSTEM' is introduced to detect change points based on the 'STEM' algorithm in D. Cheng and A. Schwartzman (2017) .

Calculate 3D Contour Meshes Using the Marching Cubes Algorithm

A port of the C++ routine for applying the marching cubes algorithm written by Thomas Lewiner et al. (2012) into an R package. The package supplies the contour3d() function, which takes a 3-dimensional array of voxel data and calculates the vertices, vertex normals, and faces for a 3d mesh representing the contour(s) at a given level.

The Multiple Filter Test for Change Point Detection

Provides statistical tests and algorithms for the detection of change points in time series and point processes - particularly for changes in the mean in time series and for changes in the rate and in the variance in point processes. References - Michael Messer, Marietta Kirchner, Julia Schiemann, Jochen Roeper, Ralph Neininger and Gaby Schneider (2014), A multiple filter test for the detection of rate changes in renewal processes with varying variance . Stefan Albert, Michael Messer, Julia Schiemann, Jochen Roeper, Gaby Schneider (2017), Multi-scale detection of variance changes in renewal processes in the presence of rate change points . Michael Messer, Kaue M. Costa, Jochen Roeper and Gaby Schneider (2017), Multi-scale detection of rate changes in spike trains with weak dependencies . Michael Messer, Stefan Albert and Gaby Schneider (2018), The multiple filter test for change point detection in time series . Michael Messer, Hendrik Backhaus, Albrecht Stroh and Gaby Schneider (2019+) Peak detection in time series.

Fast Principal Component Analysis for Outlier Detection

Methods to detect genetic markers involved in biological adaptation. 'pcadapt' provides statistical tools for outlier detection based on Principal Component Analysis. Implements the method described in (Luu, 2016) and later revised in (Privé, 2020) .

Reproducible Stimuli

Create reproducible image stimuli, specialised for face images with 'psychomorph' or 'webmorph' templates.

Functions for the Detection of Spatial Clusters of Diseases

A set of functions for the detection of spatial clusters of disease using count data. Bootstrap is used to estimate sampling distributions of statistics.

Abrupt Change-Point or Aberration Detection in Point Series

Offers an interactive function for the detection of breakpoints in series.

Implementation of the Unsupervised Smooth Contour Line Detection for Images

An implementation of the Unsupervised Smooth Contour Detection algorithm for digital images as described in the paper: "Unsupervised Smooth Contour Detection" by Rafael Grompone von Gioi, and Gregory Randall (2016). The algorithm is explained at .