The advent of genomic technologies has enabled the generation of two-dimensional or even multi-dimensional high-throughput data, e.g., monitoring multiple changes in gene expression in genome-wide siRNA screens across many different cell types (E Robert McDonald 3rd (2017) <doi: 10.1016/j.cell.2017.07.005> and Tsherniak A (2017) <doi: 10.1016/j.cell.2017.06.010>) or single cell transcriptomics under different experimental conditions. We found that simple computational methods based on a single statistical criterion is no longer adequate for analyzing such multi-dimensional data. We herein introduce ZetaSuite', a statistical package initially designed to score hits from two-dimensional RNAi screens.We also illustrate a unique utility of ZetaSuite in analyzing single cell transcriptomics to differentiate rare cells from damaged ones (Vento-Tormo R (2018) <doi: 10.1038/s41586-018-0698-6>). In ZetaSuite', we have the following steps: QC of input datasets, normalization using Z-transformation, Zeta score calculation and hits selection based on defined Screen Strength.

Access, download and locally cache files deposited on Zenodo <https://zenodo.org>.

Make working with ZIP codes in R painless with an integrated dataset of U.S. ZIP codes and functions for working with them. Search ZIP codes by multiple geographies, including state, county, city & across time zones. Also included are functions for relating ZIP codes to Census data, geocoding & distance calculations.

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>.

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>.

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>.

Fetch statistics about views, downloads and data volume from Zenodo deposits. The package collects a Zenodo (<https://zenodo.org>) deposit file information, respecting the website scrapping policies.

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 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 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>.

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>.

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.

Assesses evidence for Zipf's Law of Abbreviation in animal vocalisation using IDs, note class and note duration. The package also provides a web plot function for visualisation.

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 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.

Permutations tests to identify factor correlated to zero-inflated proportions response. Provide a performance indicator based on Spearman correlation to quantify the part of correlation explained by the selected set of factors. See details for the method at the following preprint e.g.: <https://hal.archives-ouvertes.fr/hal-02936779v3>.

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

This package provides an R wrapper for the Zendesk API.

The Zarr specification is widely used to build libraries for the storage and retrieval of n-dimensional array data from data stores ranging from local file systems to the cloud. This package is a native Zarr implementation in R with support for all required features of Zarr version 3. It is designed to be extensible such that new stores, codecs and extensions can be added easily.