This package provides utilities for computing measures to assess model quality, which are not directly provided by R's base or stats packages. These include e.g. measures like r-squared, intraclass correlation coefficient, root mean squared error or functions to check models for overdispersion, singularity or zero-inflation and more. Functions apply to a large variety of regression models, including generalized linear models, mixed effects models and Bayesian models.

The bundle provides four packages:

• rubikcube provides commands for typesetting Rubik cubes and their transformations,

• rubiktwocube provides commands for typesetting Rubik twocubes and their transformations,

• rubikrotation can process a sequence of Rubik rotation moves, with the help of a Perl package executed via \write18 (shell escape) commands,

• rubikpatterns is a collection of well known patterns and their associated rotation sequences.

Pairwise Hamming distances are computed between the rows of a binary (0/1) matrix using highly optimized C code. The input is an integer matrix where each row represents a binary feature vector and returns a symmetric integer matrix of pairwise distances. Internally, rows are bit-packed into 64-bit words for fast XOR-based comparisons, with hardware-accelerated popcount operations to count differences. OpenMP parallelization ensures efficient performance for large matrices.

Using hybrid data, this package created a vividly colored hybrid heat map. The input is two files which are auto-selected. The first file has three columns, the first two for pairs of species, with the third column for the hybrid experiment code (an integer). The second file is a list of code and their descriptions in two columns. The output is a figure showing the hybrid heat map with a color legend.

Facilitate the description, transformation, exploration, and reproducibility of metabarcoding analyses. MiscMetabar is mainly built on top of the phyloseq', dada2 and targets R packages. It helps to build reproducible and robust bioinformatics pipelines in R. MiscMetabar makes ecological analysis of alpha and beta-diversity easier, more reproducible and more powerful by integrating a large number of tools. Important features are described in Taudière A. (2023) <doi:10.21105/joss.06038>.

Code to support a systems biology research program from inception through publication. The methods focus on dimension reduction approaches to detect patterns in complex, multivariate experimental data and places an emphasis on informative visualizations. The goal for this project is to create a package that will evolve over time, thereby remaining relevant and reflective of current methods and techniques. As a result, we encourage suggested additions to the package, both methodological and graphical.

The Open University Learning Analytics Dataset (OULAD) is available from Kuzilek et al. (2017) <doi:10.1038/sdata.2017.171>. The ouladFormat package loads, cleans and formats the OULAD for data analysis (each row of the returned data set is an individual student). The packageâ s main function, combined_dataset(), allows the user to choose whether the returned data set includes assessment, demographics, virtual learning environment (VLE), or registration variables etc.

This package provides a software package help user to create virtual species for species distribution modelling. It includes several methods to help user to create virtual species distribution map. Those maps can be used for Species Distribution Modelling (SDM) study. SDM use environmental data for sites of occurrence of a species to predict all the sites where the environmental conditions are suitable for the species to persist, and may be expected to occur.

Manipulating input and output files of the STICS crop model. Files are either JavaSTICS XML files or text files used by the model fortran executable. Most basic functionalities are reading or writing parameter names and values in both XML or text input files, and getting data from output files. Advanced functionalities include XML files generation from XML templates and/or spreadsheets, or text files generation from XML files by using xslt transformation.

This package provides a hash table with consistent order and fast iteration.

The indexmap is a hash table where the iteration order of the key-value pairs is independent of the hash values of the keys. It has the usual hash table functionality, it preserves insertion order except after removals, and it allows lookup of its elements by either hash table key or numerical index. A corresponding hash set type is also provided.

This package provides a hash table with consistent order and fast iteration.

The indexmap is a hash table where the iteration order of the key-value pairs is independent of the hash values of the keys. It has the usual hash table functionality, it preserves insertion order except after removals, and it allows lookup of its elements by either hash table key or numerical index. A corresponding hash set type is also provided.

This package provides a hash table with consistent order and fast iteration.

The indexmap is a hash table where the iteration order of the key-value pairs is independent of the hash values of the keys. It has the usual hash table functionality, it preserves insertion order except after removals, and it allows lookup of its elements by either hash table key or numerical index. A corresponding hash set type is also provided.

This package provides a hash table with consistent order and fast iteration.

The indexmap is a hash table where the iteration order of the key-value pairs is independent of the hash values of the keys. It has the usual hash table functionality, it preserves insertion order except after removals, and it allows lookup of its elements by either hash table key or numerical index. A corresponding hash set type is also provided.

Developed to perform the tasks given by the following. 1-computing the probability density function and distribution function of a univariate stable distribution; 2- generating from univariate stable, truncated stable, multivariate elliptically contoured stable, and bivariate strictly stable distributions; 3- estimating the parameters of univariate symmetric stable, skew stable, Cauchy, multivariate elliptically contoured stable, and multivariate strictly stable distributions; 4- estimating the parameters of the mixture of symmetric stable and mixture of Cauchy distributions.

Convert fitted objects from various R mixed-model packages into tidy data frames along the lines of the broom package. The package provides three S3 generics for each model: tidy(), which summarizes a model's statistical findings such as coefficients of a regression; augment(), which adds columns to the original data such as predictions, residuals and cluster assignments; and glance(), which provides a one-row summary of model-level statistics.

Supports analyses using the Global Forest Change dataset released by Hansen et al. gfcanalysis was originally written for the Tropical Ecology Assessment and Monitoring (TEAM) Network. For additional details on the Global Forest Change dataset, see: Hansen, M. et al. 2013. "High-Resolution Global Maps of 21st-Century Forest Cover Change." Science 342 (15 November): 850-53. The forest change data and more information on the product is available at <http://earthenginepartners.appspot.com>.

Events from individual hydrologic time series are extracted, and events from multiple time series can be matched to each other. Tang, W. & Carey, S. K. (2017) <doi:10.1002/hyp.11185>. Kaur, S., Horne, A., Stewardson, M.J., Nathan, R., Costa, A.M., Szemis, J.M., & Webb, J.A. (2017) <doi:10.1080/24705357.2016.1276418>. Ladson, A., Brown, R., Neal, B., & Nathan, R. J. (2013) <doi:10.7158/W12-028.2013.17.1>.

Provide methods to perform customized inference at individual level by taking contextual covariates into account. Three main functions are provided in this package: (i) LASER(): it generates specially-designed artificial relevant samples for a given case; (ii) g2l.proc(): computes customized fdr(z|x); and (iii) rEB.proc(): performs empirical Bayes inference based on LASERs. The details can be found in Mukhopadhyay, S., and Wang, K (2021, <arXiv:2004.09588>).

Estimating causal parameters in the presence of treatment spillover is of great interest in statistics. This package provides tools for instrumental variables estimation of average causal effects under network interference of unknown form. The target parameters are the local average direct effect, the local average indirect effect, the local average overall effect, and the local average spillover effect. The methods are developed by Hoshino and Yanagi (2023) <doi:10.48550/arXiv.2108.07455>.

Create dummy variables from categorical data. This package can convert categorical data (factor and ordered) into dummy variables and handle multiple columns simultaneously. This package enables to select whether a dummy variable for base group is included (for principal component analysis/factor analysis) or excluded (for regression analysis) by an option. makedummies function accepts data.frame', matrix', and tbl (tibble) class (by tibble package). matrix class data is automatically converted to data.frame class.

The temporal relationship between motor neurons can offer explanations for neural strategies. We combined functions to reduce neuron action potential discharge data and analyze it for short-term, time-domain synchronization. Even more so, motoRneuron combines most available methods for the determining cross correlation histogram peaks and most available indices for calculating synchronization into simple functions. See Nordstrom, Fuglevand, and Enoka (1992) <doi:10.1113/jphysiol.1992.sp019244> for a more thorough introduction.

Evaluate hypotheses concerning the distribution of multinomial proportions using bridge sampling. The bridge sampling routine is able to compute Bayes factors for hypotheses that entail inequality constraints, equality constraints, free parameters, and mixtures of all three. These hypotheses are tested against the encompassing hypothesis, that all parameters vary freely or against the null hypothesis that all category proportions are equal. For more information see Sarafoglou et al. (2020) <doi:10.31234/osf.io/bux7p>.

Datasets and functions to benchmark (convergence, speed, ease of use) R packages dedicated to regression with neural networks (no classification in this version). The templates for the tested packages are available in the R, R Markdown and HTML formats at <https://github.com/pkR-pkR/NNbenchmarkTemplates> and <https://theairbend3r.github.io/NNbenchmarkWeb/index.html>. The submitted article to the R-Journal can be read at <https://www.inmodelia.com/gsoc2020.html>.

This is a collection of data and functions for common metrics in political science research. Data measuring ideology, and functions calculating geographical diffusion and ideological diffusion - geog.diffuse() and ideo.dist(), respectively. Functions derived from methods developed in: Soule and King (2006) <doi:10.1086/499908>, Berry et al. (1998) <doi:10.2307/2991759>, Cruz-Aceves and Mallinson (2019) <doi:10.1177/0160323X20902818>, and Grossback et al. (2004) <doi:10.1177/1532673X04263801>.