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>.

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.

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 MCMC algorithms for the analysis of zero-inflated count models. The case of stochastic search variable selection (SVS) is also considered. All MCMC samplers are coded in C++ for improved efficiency. A data set considering the demand for health care is provided.

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

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.

Implementation of zero-inflated Poisson models under Bayesian framework using data augmentation as discussed in Chapter 5 of Zhang (2020) <https://hdl.handle.net/10012/16378>. This package is constructed in accommodating four different scenarios: the general scenario, the scenario with measurement error in responses, the external validation scenario, and the internal validation scenario.

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).

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.

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>.

We provide a flexible Zero-inflated Poisson-Gamma Model (ZIPG) by connecting both the mean abundance and the variability to different covariates, and build valid statistical inference procedures for both parameter estimation and hypothesis testing. These functions can be used to analyze microbiome count data with zero-inflation and overdispersion. The model is discussed in Jiang et al (2023) <doi:10.1080/01621459.2022.2151447>.

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>.

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

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.

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.