Computes the product moments of the truncated multivariate normal distribution, particularly for cases involving patterned variance-covariance matrices. It also has the capability to calculate these moments with arbitrary positive-definite matrices, although performance may degrade for high-dimensional variables.

Simplifies access to Tunisian government open data from <https://data.gov.tn/fr/>. Queries datasets by theme, author, or keywords, retrieves metadata, and gets structured results ready for analysis; all through the official CKAN API.

This package implements the TabNet model by Sercan O. Arik et al. (2019) <doi:10.48550/arXiv.1908.07442> with Coherent Hierarchical Multi-label Classification Networks by Giunchiglia et al. <doi:10.48550/arXiv.2010.10151> and provides a consistent interface for fitting and creating predictions. It's also fully compatible with the tidymodels ecosystem.

This package provides three estimators for tensor response regression (TRR) and tensor predictor regression (TPR) models with tensor envelope structure. The three types of estimation approaches are generic and can be applied to any envelope estimation problems. The full Grassmannian (FG) optimization is often associated with likelihood-based estimation but requires heavy computation and good initialization; the one-directional optimization approaches (1D and ECD algorithms) are faster, stable and does not require carefully chosen initial values; the SIMPLS-type is motivated by the partial least squares regression and is computationally the least expensive. For details of TRR, see Li L, Zhang X (2017) <doi:10.1080/01621459.2016.1193022>. For details of TPR, see Zhang X, Li L (2017) <doi:10.1080/00401706.2016.1272495>. For details of 1D algorithm, see Cook RD, Zhang X (2016) <doi:10.1080/10618600.2015.1029577>. For details of ECD algorithm, see Cook RD, Zhang X (2018) <doi:10.5705/ss.202016.0037>. For more details of the package, see Zeng J, Wang W, Zhang X (2021) <doi:10.18637/jss.v099.i12>.

Turn complex JSON data into tidy data frames.

This package provides tools to calculate stability indices with parametric, non-parametric and probabilistic approaches. The basic data format requirement for toolStability is a data frame with 3 columns including numeric trait values, genotype,and environmental labels. Output format of each function is the dataframe with chosen stability index for each genotype. Function "table_stability" offers the summary table of all stability indices in this package. This R package toolStability is part of the main publication: Wang, Casadebaig and Chen (2023) <doi:10.1007/s00122-023-04264-7>. Analysis pipeline for main publication can be found on github: <https://github.com/Illustratien/Wang_2023_TAAG>. Sample dataset in this package is derived from another publication: Casadebaig P, Zheng B, Chapman S et al. (2016) <doi:10.1371/journal.pone.0146385>. For detailed documentation of dataset, please see on Zenodo <doi:10.5281/zenodo.4729636>. Indices used in this package are from: Döring TF, Reckling M (2018) <doi:10.1016/j.eja.2018.06.007>. Eberhart SA, Russell WA (1966) <doi:10.2135/cropsci1966.0011183X000600010011x>. Eskridge KM (1990) <doi:10.2135/cropsci1990.0011183X003000020025x>. Finlay KW, Wilkinson GN (1963) <doi:10.1071/AR9630742>. Hanson WD (1970) Genotypic stability. <doi:10.1007/BF00285245>. Lin CS, Binns MR (1988). Nassar R, Hühn M (1987). Pinthus MJ (1973) <doi:10.1007/BF00021563>. Römer T (1917). Shukla GK (1972). Wricke G (1962).

This package provides methods and tools for generating forecasts at different temporal frequencies using a hierarchical time series approach.

Reconstruct phylogenetic trees from discrete data. Inapplicable character states are handled using the algorithm of Brazeau, Guillerme and Smith (2019) <doi:10.1093/sysbio/syy083> with the "Morphy" library, under equal or implied step weights. Contains a "shiny" user interface for interactive tree search and exploration of results, including character visualization, rogue taxon detection, tree space mapping, and cluster consensus trees (Smith 2022a, b) <doi:10.1093/sysbio/syab099>, <doi:10.1093/sysbio/syab100>. Profile Parsimony (Faith and Trueman, 2001) <doi:10.1080/10635150118627>, Successive Approximations (Farris, 1969) <doi:10.2307/2412182> and custom optimality criteria are implemented.

Allows forecasting time series using nearest neighbors regression Francisco Martinez, Maria P. Frias, Maria D. Perez-Godoy and Antonio J. Rivera (2019) <doi:10.1007/s10462-017-9593-z>. When the forecasting horizon is higher than 1, two multi-step ahead forecasting strategies can be used. The model built is autoregressive, that is, it is only based on the observations of the time series. The nearest neighbors used in a prediction can be consulted and plotted.

An implementation of turtle graphics <http://en.wikipedia.org/wiki/Turtle_graphics>. Turtle graphics comes from Papert's language Logo and has been used to teach concepts of computer programming.

Download TIGER/Line shapefiles from the United States Census Bureau (<https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html>) and load into R as sf objects.

This package provides convenience functions for common data modification and analysis tasks in communication research. This includes functions for univariate and bivariate data analysis, index generation and reliability computation, and intercoder reliability tests. All functions follow the style and syntax of the tidyverse, and are construed to perform their computations on multiple variables at once. Functions for univariate and bivariate data analysis comprise summary statistics for continuous and categorical variables, as well as several tests of bivariate association including effect sizes. Functions for data modification comprise index generation and automated reliability analysis of index variables. Functions for intercoder reliability comprise tests of several intercoder reliability estimates, including simple and mean pairwise percent agreement, Krippendorff's Alpha (Krippendorff 2004, ISBN: 9780761915454), and various Kappa coefficients (Brennan & Prediger 1981 <doi: 10.1177/001316448104100307>; Cohen 1960 <doi: 10.1177/001316446002000104>; Fleiss 1971 <doi: 10.1037/h0031619>).

Interactive laboratory of Time Series based in Box-Jenkins methodology.

Access Open Trade Statistics API from R to download international trade data.

This package provides tools for the exploration of distributions of phylogenetic trees. This package includes a shiny interface which can be started from R using treespaceServer(). For further details see Jombart et al. (2017) <DOI:10.1111/1755-0998.12676>.

This package implements a method for identifying subgroups with superior response relative to the overall sample.

In some phase I trials, the design goal is to find the dose associated with a certain target toxicity rate or the dose with a certain weighted sum of rates of various toxicity grades. TITEgBOIN provides the set up and calculations needed to run a dose-finding trial using bayesian optimal interval (BOIN) (Yuan et al. (2016) <doi:10.1158/1078-0432.CCR-16-0592>), generalized bayesian optimal interval (gBOIN) (Mu et al. (2019) <doi:10.1111/rssc.12263>), time-to-event bayesian optimal interval (TITEBOIN) (Lin et al. (2020) <doi:10.1093/biostatistics/kxz007>) and time-to-event generalized bayesian optimal interval (TITEgBOIN) (Takeda et al. (2022) <doi:10.1002/pst.2182>) designs. TITEgBOIN can conduct tasks: run simulations and get operating characteristics; determine the dose for the next cohort; select maximum tolerated dose (MTD). These functions allow customization of design characteristics to vary sample size, cohort sizes, target dose limiting toxicity (DLT) rates or target normalized equivalent toxicity score (ETS) rates to account for discrete toxicity score, and incorporate safety and/or stopping rules.

This package provides a constrained two-dimensional Delaunay triangulation package providing both triangulation and generation of voronoi mosaics of irregular spaced data. Please note that most of the functions are now also covered in package interp, which is a re-implementation from scratch under a free license based on a different triangulation algorithm.

An R shiny app designed for diverse text analysis tasks, offering a wide range of methodologies tailored to Natural Language Processing (NLP) needs. It is a versatile, general-purpose tool for analyzing textual data. tall features a comprehensive workflow, including data cleaning, preprocessing, statistical analysis, and visualization, all integrated for effective text analysis.

Evaluation of alternatives based on multiple criteria using TOPSIS method.

The Upsilon test assesses association among categorical variables against the null hypothesis of independence (Luo 2021 MS thesis; ProQuest Publication No. 28649813). While promoting dominant function patterns, it demotes non-dominant function patterns. It is robust to low expected count---continuity correction like Yates's seems unnecessary. Using a common null population following a uniform distribution, contingency tables are comparable by statistical significance---not the case for most association tests defining a varying null population by tensor product of observed marginals. Although Pearson's chi-squared test, Fisher's exact test, and Woolf's G-test (related to mutual information) are useful in some contexts, the Upsilon test appeals to ranking association patterns not necessarily following same marginal distributions, such as in count data from DNA and RNA sequencing---a rapidly expanding frontier in modern science.

This package provides functions for building customized ready-to-export tables for publication.

This is a framework that aims to provide methods and tools for assessing the impact of different sources of uncertainties (e.g.positional uncertainty) on performance of species distribution models (SDMs).).

Programmatic interface to access data from the UK Health Security Agency (UKHSA) Data Dashboard API. The package was originally based on the ukcovid19 package by Pouria Hadjibagheri and has been substantially rewritten and extended. For more information on the API, see <https://ukhsa-dashboard.data.gov.uk/access-our-data>.