Tree-structured modelling of categorical predictors (Tutz and Berger (2018), <doi:10.1007/s11634-017-0298-6>) or measurement units (Berger and Tutz (2018), <doi:10.1080/10618600.2017.1371030>).

Extract glyph information from font data, and translate the outline curves to flattened paths or tessellated polygons. The converted data is returned as a data.frame in easy-to-plot format.

Includes built-in methods for generating long SQL CASE statements, and other SQL statements that may otherwise be arduous to construct by hand.The generated statement can easily be concatenated to string literals to form queries to SQL'-like databases, such as when using the RODBC package. The current methods include casewhen() for building CASE statements, inlist() for building IN statements, and updatetable() for building UPDATE statements.

This package implements the smooth LASSO estimator for the function-on-function linear regression model described in Centofanti et al. (2022) <doi:10.1016/j.csda.2022.107556>.

This package provides influence function-based methods to evaluate a longitudinal surrogate marker in a censored time-to-event outcome setting, with plug-in and targeted maximum likelihood estimation options. Details are described in: Agniel D and Parast L (2025). "Robust Evaluation of Longitudinal Surrogate Markers with Censored Data." Journal of the Royal Statistical Society: Series B <doi:10.1093/jrsssb/qkae119>. A tutorial for this package can be found at <https://www.laylaparast.com/survivalsurrogate> and a Shiny App implementing the package can be found at <https://parastlab.shinyapps.io/survivalsurrogateApp/>.

This package provides a user-friendly wrapper for web automation, using either chromote or selenium'. Provides a simple and consistent API to make web scraping and testing scripts easy to write and understand. Elements are lazy, and automatically wait for the website to be valid, resulting in reliable and reproducible code, with no visible impact on the experience of the programmer.

Includes functions for interacting with common meta data fields, writing insert statements, calling functions, and more for T-SQL and Postgresql'.

This package provides a small set of functions wrapping up the call stack and command line inspection needed to determine a running script's filename from within the script itself.

This package provides a pair of functions that allow for the generation and tracking of coordinate data clouds without a time dimension, primarily for use in super-resolution plant micro-tubule image segmentation.

Print function signatures and find overly complicated code.

This package provides functions to retrieve, process, analyze, and quality-control marine physical, chemical, and biological data. The main focus is on Swedish monitoring data available through the SHARK database <https://shark.smhi.se/en/>, with additional API support for Nordic Microalgae <https://nordicmicroalgae.org/>, Dyntaxa <https://artfakta.se/>, World Register of Marine Species ('WoRMS') <https://www.marinespecies.org>, AlgaeBase <https://www.algaebase.org>, OBIS xylookup web service <https://iobis.github.io/xylookup/> and Intergovernmental Oceanographic Commission (IOC) - UNESCO databases on harmful algae <https://www.marinespecies.org/hab/> and toxins <https://toxins.hais.ioc-unesco.org/>.

This package provides a set of spatial accessibility measures from a set of locations (demand) to another set of locations (supply). It aims, among others, to support research on spatial accessibility to health care facilities. Includes the locations and some characteristics of major public hospitals in Greece.

Perform spatial temporal analysis of moving polygons; a longstanding analysis problem in Geographic Information Systems. Facilitates directional analysis, distance analysis, and some other simple functionality for examining spatial-temporal patterns of moving polygons.

Simulate and plot general experimental crosses. The focus is on simulating genotypes with an aim towards flexibility rather than speed. Meiosis is simulated following the Stahl model, in which chiasma locations are the superposition of two processes: a proportion p coming from a process exhibiting no interference, and the remainder coming from a process following the chi-square model.

Fits, spatially predicts and temporally forecasts large amounts of space-time data using [1] Bayesian Gaussian Process (GP) Models, [2] Bayesian Auto-Regressive (AR) Models, and [3] Bayesian Gaussian Predictive Processes (GPP) based AR Models for spatio-temporal big-n problems. Bakar and Sahu (2015) <doi:10.18637/jss.v063.i15>.

This package provides a step-down procedure for controlling the False Discovery Proportion (FDP) in a competition-based setup, implementing Dong et al. (2020) <arXiv:2011.11939>. Such setups include target-decoy competition (TDC) in computational mass spectrometry and the knockoff construction in linear regression.

Setaria viridis (green foxtail) is a common weed. This package contains measurements from individual branches of a wild Setaria viridis plant collected near the author's home. The data is intended for use in data analysis practice.

This package provides a systematic bioinformatics tool to perform single-sample mutation-based pathway analysis by integrating somatic mutation data with the Protein-Protein Interaction (PPI) network. In this method, we use local and global weighted strategies to evaluate the effects of network genes from mutations according to the network topology and then calculate the mutation-based pathway enrichment score (ssMutPES) to reflect the accumulated effect of mutations of each pathway. Subsequently, the ssMutPES profiles are used for unsupervised spectral clustering to identify cancer subtypes.

This package provides functions for converting and processing network data from a SpatialLinesDataFrame -Class object to an igraph'-Class object.

All data in the book "Statistical Methods in Biology" by Welham et al. (2015) <doi:10.1201/b17336> with a corresponding documentation and illustrative analysis of the data.

This package provides a collection of functions for reading soil data from U.S. Department of Agriculture Natural Resources Conservation Service (USDA-NRCS) and National Cooperative Soil Survey (NCSS) databases.

The synchrosqueezed wavelet transform is implemented. The package is a translation of MATLAB Synchrosqueezing Toolbox, version 1.1 originally developed by Eugene Brevdo (2012). The C code for curve_ext was authored by Jianfeng Lu, and translated to Fortran by Dongik Jang. Synchrosqueezing is based on the papers: [1] Daubechies, I., Lu, J. and Wu, H. T. (2011) Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool. Applied and Computational Harmonic Analysis, 30. 243-261. [2] Thakur, G., Brevdo, E., Fukar, N. S. and Wu, H-T. (2013) The Synchrosqueezing algorithm for time-varying spectral analysis: Robustness properties and new paleoclimate applications. Signal Processing, 93, 1079-1094.

This package contains more modern tools for causal inference using regression standardization. Four general classes of models are implemented; generalized linear models, conditional generalized estimating equation models, Cox proportional hazards models, and shared frailty gamma-Weibull models. Methodological details are described in Sjölander, A. (2016) <doi:10.1007/s10654-016-0157-3>. Also includes functionality for doubly robust estimation for generalized linear models in some special cases, and the ability to implement custom models.

Models the nonnegative entries of a rectangular adjacency matrix using a sparse latent position model, as illustrated in Rastelli, R. (2018) "The Sparse Latent Position Model for nonnegative weighted networks" <arXiv:1808.09262>.