Implementation of new statistical distributions in (0, 1) interval. Each distribution includes the traditional functions as well as an additional function called the family function, which can be used to estimate parameters using Generalized Additive Models for Location, Scale and Shape, GAMLSS by Rigby & Stasinopoulos (2005) <doi:10.1111/j.1467-9876.2005.00510.x>.

This package provides simple statistics from instruments and observations at sites in the NEON network, and acts as a simple interface for v0 of the National Ecological Observatory Network (NEON) API. Statistics are generated for meteorologic and soil-based observations, and are presented for daily, annual, and one-time observations at all available NEON sites. Users can also retrieve any dataset publicly hosted by NEON. Metadata for NEON sites and data products can be returned, as well as information on data product availability by site and date. For more information on NEON, please visit <https://www.neonscience.org>. For detailed data product information, please see the NEON data product catalog at <https://data.neonscience.org/data-product-catalog>.

This package implements Python-style zip for R. Is a more flexible version of cbind.

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>.

This package provides a set of functions for working with American postal codes, which are known as ZIP Codes. These include accessing ZIP Code to ZIP Code Tabulation Area (ZCTA) crosswalks, retrieving demographic data for ZCTAs, and tabulating demographic data for three-digit ZCTAs.

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

This package provides an Interface to Zenodo (<https://zenodo.org>) REST API, including management of depositions, attribution of DOIs by Zenodo and upload and download of files.

Use behavioural variables to compute period, rhythmicity and other circadian parameters. Methods include computation of chi square periodograms (Sokolove and Bushell (1978) <DOI:10.1016/0022-5193(78)90022-X>), Lomb-Scargle periodograms (Lomb (1976) <DOI:10.1007/BF00648343>, Scargle (1982) <DOI:10.1086/160554>, Ruf (1999) <DOI:10.1076/brhm.30.2.178.1422>), and autocorrelation-based periodograms.

This package provides functions to compute compositional turnover using zeta-diversity, the number of species shared by multiple assemblages. The package includes functions to compute zeta-diversity for a specific number of assemblages and to compute zeta-diversity for a range of numbers of assemblages. It also includes functions to explain how zeta-diversity varies with distance and with differences in environmental variables between assemblages, using generalised linear models, linear models with negative constraints, generalised additive models,shape constrained additive models, and I-splines.

This package provides a two-part zero-inflated Beta regression model with random effects (ZIBR) for testing the association between microbial abundance and clinical covariates for longitudinal microbiome data. Eric Z. Chen and Hongzhe Li (2016) <doi:10.1093/bioinformatics/btw308>.

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>.

Statistical models and utilities for the analysis of word frequency distributions. The utilities include functions for loading, manipulating and visualizing word frequency data and vocabulary growth curves. The package also implements several statistical models for the distribution of word frequencies in a population. (The name of this package derives from the most famous word frequency distribution, Zipf's law.).

Facilitates making a connection to the Zendesk API and executing various queries. You can use it to get ticket, ticket metrics, and user data. The Zendesk documentation is available at <https://developer.zendesk.com/rest_api /docs/support/introduction>. This package is not supported by Zendesk (owner of the software).

Facilitates making a connection to the Zoom API and executing various queries. You can use it to get data on Zoom webinars and Zoom meetings. The Zoom documentation is available at <https://developers.zoom.us/docs/api/>. This package is not supported by Zoom (owner of the software).

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.

This package provides tools for estimating Zero-Inflated INAR(1) (ZI-INAR(1)) and Hurdle INAR(1) (H-INAR(1)) models using Stan'. It allows users to simulate time series data for these models, estimate parameters, and evaluate model fit using various criteria. Functions include model estimation, simulation, and likelihood-based metrics.

Parameter estimation for zero-inflated discrete Weibull (ZIDW) regression models, the univariate setting, distribution functions, functions to generate randomized quantile residuals a pseudo R2, and plotting of rootograms. For more details, see Kalktawi (2017) <https://bura.brunel.ac.uk/handle/2438/14476>, Taconeli and Rodrigues de Lara (2022) <doi:10.1080/00949655.2021.2005597>, and Yeh and Young (2025) <doi:10.1080/03610918.2025.2464076>.

This function produces empirical best linier unbiased predictions (EBLUPs) for Zero-Inflated data and its Relative Standard Error. Small Area Estimation with Zero-Inflated Model (SAE-ZIP) is a model developed for Zero-Inflated data that can lead us to overdispersion situation. To handle this kind of situation, this model is created. The model in this package is based on Small Area Estimation with Zero-Inflated Poisson model proposed by Dian Christien Arisona (2018)<https://repository.ipb.ac.id/handle/123456789/92308>. For the data sample itself, we use combination method between Roberto Benavent and Domingo Morales (2015)<doi:10.1016/j.csda.2015.07.013> and Sabine Krieg, Harm Jan Boonstra and Marc Smeets (2016)<doi:10.1515/jos-2016-0051>.

This package provides a structured framework for consistent user communication and configuration management for package developers.

This package implements the estimation of local (and global) association measures: Lewontin's D, Ducher's Z, pointwise mutual information, normalized pointwise mutual information and chi-squared residuals. The significance of local (and global) association is accessed using p-values estimated by permutations.

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>.

Generates Realizations of First-Order Integer Valued Autoregressive Processes with Zero-Inflated Innovations (ZINAR(1)) and Estimates its Parameters as described in Garay et al. (2021) <doi:10.1007/978-3-030-82110-4_2>.

This package implements zero-modified versions of the Complex Tri-Parametric Pearson distribution for overdispersed count data. The package addresses limitations of existing implementations when the parameter b approaches zero. It provides distribution functions, maximum likelihood estimation, and diagnostic tools for modeling count data with excess zeros. The methodology is based on Rodriguez-Avi and coauthors (2003) <doi:10.1007/s00362-002-0134-7>.

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>.