An interface to Zonation software, enabling users to run spatial conservation prioritization workflows in R'. It streamlines input preparation, execution, and post-processing, while supporting reproducibility and lowering the entry barrier for learning, teaching, and research in conservation planning. The methods implemented in Zonation are described in Moilanen et al. (2022) <doi:10.1111/2041-210X.13819>.

Estimation methods for zero-inflated Poisson factor analysis (ZIPFA) on sparse data. It provides estimates of coefficients in a new type of zero-inflated regression. It provides a cross-validation method to determine the potential rank of the data in the ZIPFA and conducts zero-inflated Poisson factor analysis based on the determined rank.

Graphical tools for visualizing high-dimensional data along a path of alternating one- and two-dimensional plots. Includes optional interactive graphics via loon (which uses tcltk from base R). Support is provided for constructing graph structures and, when available, plotting them with Bioconductor packages (e.g., graph', Rgraphviz'); these are optional and examples/vignettes are skipped if they are not installed. For algorithms and further details, see <doi:10.18637/jss.v095.i04>.

This package provides a suite of statistics for identifying areas of the genome under selective pressure. See Jacobs, Sluckin and Kivisild (2016) <doi:10.1534/genetics.115.185900>.

Simulation, exploratory data analysis and Bayesian analysis of the p-order Integer-valued Autoregressive (INAR(p)) and Zero-inflated p-order Integer-valued Autoregressive (ZINAR(p)) processes, as described in Garay et al. (2020) <doi:10.1080/00949655.2020.1754819>.

Computes a zonohedron from real vector generators. The package also computes zonogons (2D zonotopes) and zonosegs (1D zonotopes). An elementary S3 class for matroids is included, which supports matroids with rank 3, 2, and 1. Optimization methods are taken from Heckbert (1985) <https://www.cs.cmu.edu/~ph/zono.ps.gz>.

This package provides an R wrapper for the Zendesk API.

Geneâ based association tests to model count data with excessive zeros and rare variants using zero-inflated Poisson/zero-inflated negative Binomial regression framework. This method was originally described by Fan, Sun, and Li in Genetic Epidemiology 46(1):73-86 <doi:10.1002/gepi.22438>.

Implementation of four extensions of the Zipf distribution: the Marshall-Olkin Extended Zipf (MOEZipf) Pérez-Casany, M., & Casellas, A. (2013) <arXiv:1304.4540>, the Zipf-Poisson Extreme (Zipf-PE), the Zipf-Poisson Stopped Sum (Zipf-PSS) and the Zipf-Polylog distributions. In log-log scale, the two first extensions allow for top-concavity and top-convexity while the third one only allows for top-concavity. All the extensions maintain the linearity associated with the Zipf model in the tail.

This tool provides functions to load, segment and classify zooplankton images. The image processing algorithms and the machine learning classifiers in this package are (will be, since these have not been added yet) direct ports of an early python implementation that can be found at <https://github.com/arickGrootveld/ZooID>. The model weights and datasets (also not added yet) that are a part of this package can also be found at Arick Grootveld, Eva R. Kozak, Carmen Franco-Gordo (2023) <doi:10.5281/zenodo.7979996>.

Procedures for calculation, plotting, animation, and approximation of the outputs for fuzzy numbers (see A.I. Ban, L. Coroianu, P. Grzegorzewski "Fuzzy Numbers: Approximations, Ranking and Applications" (2015)) based on the Zadeh's Extension Principle (see de Barros, L.C., Bassanezi, R.C., Lodwick, W.A. (2017) <doi:10.1007/978-3-662-53324-6_2>).

This package provides fast and easy access to German census grid data from the 2011 and 2022 censuses <https://www.zensus2022.de/>, including a wide range of socio-economic indicators at multiple spatial resolutions (100m, 1km, 10km). Enables efficient download, processing, and analysis of large census datasets covering population, households, families, dwellings, and buildings. Harmonized data structures allow direct comparison with the 2011 census, supporting temporal and spatial analyses. Facilitates conversion of data into common formats for spatial analysis and mapping ('terra', sf', ggplot2').

Utilities for simplifying common statistical operations including probability density functions, cumulative distribution functions, Kolmogorov-Smirnov tests, principal component analysis plots, and prediction plots.

Uses bootstrap to test zero order correlation being equal to a partial or semi-partial correlation (one or two tailed). Confidence intervals for the parameter (zero order minus partial) can also be determined. Implements the bias-corrected and accelerated bootstrap method as described in "An Introduction to the Bootstrap" Efron (1983) <0-412-04231-2>.

An implementation of z-curves - a method for estimating expected discovery and replicability rates on the bases of test-statistics of published studies. The package provides functions for fitting the density, EM, and censored EM version (Bartoš & Schimmack, 2022, <doi:10.15626/MP.2021.2720>; Schimmack & Bartoš, 2023, <doi: 10.1371/journal.pone.0290084>), as well as the original density z-curve (Brunner & Schimmack, 2020, <doi:10.15626/MP.2018.874>). Furthermore, the package provides summarizing and plotting functions for the fitted z-curve objects. See the aforementioned articles for more information about the z-curves, expected discovery and replicability rates, validation studies, and limitations.

Converts double-precision floating-point values to decimal strings with the shortest significands needed for round-trip recovery. Uses the zmij algorithm through a vendored Rust implementation. The method is described in Zverovich (2025), "Faster Double-to-String Conversion" <https://vitaut.net/posts/2025/faster-dtoa/>. Provides vectorized formatting, a correctly rounded inverse parser, and explicit handling of missing and non-finite values.