Quaternions Splines

Provides routines to create some quaternions splines: Barry-Goldman algorithm, De Casteljau algorithm, and Kochanek-Bartels algorithm. The implementations are based on the Python library 'splines'. Quaternions splines allow to construct spherical curves. References: Barry and Goldman , Kochanek and Bartels .

A Time Series Toolbox for Official Statistics

Plot official statistics' time series conveniently: automatic legends, highlight windows, stacked bar chars with positive and negative contributions, sum-as-line option, two y-axes with automatic horizontal grids that fit both axes and other popular chart types. 'tstools' comes with a plethora of defaults to let you plot without setting an abundance of parameters first, but gives you the flexibility to tweak the defaults. In addition to charts, 'tstools' provides a super fast, 'data.table' backed time series I/O that allows the user to export / import long format, wide format and transposed wide format data to various file types.

A Sound Interface for R

Basic functions for dealing with wav files and sound samples.

Dropout Analysis by Condition

Analysis and visualization of dropout between conditions in surveys and (online) experiments. Features include computation of dropout statistics, comparing dropout between conditions (e.g. Chi square), analyzing survival (e.g. Kaplan-Meier estimation), comparing conditions with the most different rates of dropout (Kolmogorov-Smirnov) and visualizing the result of each in designated plotting functions. Sources: Andrea Frick, Marie-Terese Baechtiger & Ulf-Dietrich Reips (2001) < https://www.researchgate.net/publication/223956222_Financial_incentives_personal_information_and_drop-out_in_online_studies>; Ulf-Dietrich Reips (2002) "Standards for Internet-Based Experimenting" .

Item Pool Visualization

Generate plots based on the Item Pool Visualization concept for latent constructs. Item Pool Visualizations are used to display the conceptual structure of a set of items (self-report or psychometric). Dantlgraber, Stieger, & Reips (2019) .

Client Interface for 'openEO' Servers

Access data and processing functionalities of 'openEO' compliant back-ends in R.

TraMineR Extension

Collection of ancillary functions and utilities to be used in conjunction with the 'TraMineR' package for sequence data exploration. Includes, among others, specific functions such as state survival plots, position-wise group-typical states, dynamic sequence indicators, and dissimilarities between event sequences. Also includes contributions by non-members of the TraMineR team such as methods for polyadic data and for the comparison of groups of sequences.

Estimating the Parameters of a Continuous-Time Markov Chain from Discrete-Time Data

Estimation of Markov generator matrices from discrete-time observations. The implemented approaches comprise diagonal and weighted adjustment of matrix logarithm based candidate solutions as in Israel (2001) as well as a quasi-optimization approach. Moreover, the expectation-maximization algorithm and the Gibbs sampling approach of Bladt and Sorensen (2005) are included.

Predict Regional Community Composition

Predict regional community composition at a fine spatial resolution using only sparse biological and environmental data. The package is based on the DynamicFOAM algorithm described in Mokany et al. (2011) .

Robust Time Series Filters

Implementations for several robust procedures that allow for (online) extraction of the signal of univariate or multivariate time series by applying robust regression techniques to a moving time window are provided. Included are univariate filtering procedures based on repeated-median regression as well as hybrid and trimmed filters derived from it; see Schettlinger et al. (2006) . The adaptive online repeated median by Schettlinger et al. (2010) and the slope comparing adaptive repeated median by Borowski and Fried (2013) choose the width of the moving time window adaptively. Multivariate versions are also provided; see Borowski et al. (2009) for a multivariate online adaptive repeated median and Borowski (2012) for a multivariate slope comparing adaptive repeated median. Furthermore, a repeated-median based filter with automatic outlier replacement and shift detection is provided; see Fried (2004) .