Sampling from the Cholesky factorization of a Wishart random variable, sampling from the inverse Wishart distribution, sampling from the Cholesky factorization of an inverse Wishart random variable, sampling from the pseudo Wishart distribution, sampling from the generalized inverse Wishart distribution, computing densities for the Wishart and inverse Wishart distributions, and computing the multivariate gamma and digamma functions. Provides a header file so the C functions can be called directly from other programs.
Built by Hodges lab members for current and future Hodges lab members. Other individuals are welcome to use as well. Provides useful functions that the lab uses everyday to analyze various genomic datasets. Critically, only general use functions are provided; functions specific to a given technique are reserved for a separate package. As the lab grows, we expect to continue adding functions to the package to build on previous lab members code.
Estimates models that extend the standard GLM to take misclassification into account. The models require side information from a secondary data set on the misclassification process, i.e. some sort of misclassification probabilities conditional on some common covariates. A detailed description of the algorithm can be found in Dlugosz, Mammen and Wilke (2015) <https://www.zew.de/publikationen/generalised-partially-linear-regression-with-misclassified-data-and-an-application-to-labour-market-transitions>.
Enhances mlexperiments <https://CRAN.R-project.org/package=mlexperiments> with additional machine learning ('ML') learners for survival analysis. The package provides R6-based survival learners for the following algorithms: glmnet <https://CRAN.R-project.org/package=glmnet>, ranger <https://CRAN.R-project.org/package=ranger>, xgboost <https://CRAN.R-project.org/package=xgboost>, and rpart <https://CRAN.R-project.org/package=rpart>. These can be used directly with the mlexperiments R package.
This package provides a collection of NASCAR race, driver, owner and manufacturer data across the three major NASCAR divisions: NASCAR Cup Series, NASCAR Xfinity Series, and NASCAR Craftsman Truck Series. The curated data begins with the 1949 season and extends through the end of the 2024 season. Explore race, season, or career performance for drivers, teams, and manufacturers throughout NASCAR's history. Data was sourced with permission from DriverAverages.com
.
Given a dataset, the user is invited to utilize the Empirical Cumulative Distribution Function (ECDF) to guess interactively the mean and the mean deviation. Thereafter, using the quadratic curve the user can guess the Root Mean Squared Deviation (RMSD) and visualize the standard deviation (SD). For details, see Sarkar and Rashid (2019)<doi:10.3126/njs.v3i0.25574>, Have You Seen the Standard Deviaton?, Nepalese Journal of Statistics, Vol. 3, 1-10.
It performs the smoothing approach provided by penalized least squares for univariate and bivariate time series, as proposed by Guerrero (2007) and Gerrero et al. (2017). This allows to estimate the time series trend by controlling the amount of resulting (joint) smoothness. --- Guerrero, V.M (2007) <DOI:10.1016/j.spl.2007.03.006>. Guerrero, V.M; Islas-Camargo, A. and Ramirez-Ramirez, L.L. (2017) <DOI:10.1080/03610926.2015.1133826>.
Converts text into speech using various text-to-speech (TTS) engines and provides an unified interface for accessing their functionality. With this package, users can easily generate audio files of spoken words, phrases, or sentences from plain text data. The package supports multiple TTS engines, including Google's Cloud Text-to-Speech API', Amazon Polly', Microsoft's Cognitive Services Text to Speech REST API', and a free TTS engine called Coqui TTS'.
Leveraging (large) language models for automatic topic labeling. The main function converts a list of top terms into a label for each topic. Hence, it is complementary to any topic modeling package that produces a list of top terms for each topic. While human judgement is indispensable for topic validation (i.e., inspecting top terms and most representative documents), automatic topic labeling can be a valuable tool for researchers in various scenarios.
This package allows to estimate chronological and gestational DNA methylation (DNAm) age as well as biological age using different methylation clocks. Chronological DNAm age (in years) : Horvath's clock, Hannum's clock, BNN, Horvath's skin+blood clock, PedBE
clock and Wu's clock. Gestational DNAm age : Knight's clock, Bohlin's clock, Mayne's clock and Lee's clocks. Biological DNAm clocks : Levine's clock and Telomere Length's clock.
An automated pipeline for the detection, integration and reporting of predefined features across a large number of mass spectrometry data files. It enables the real time annotation of multiple compounds in a single file, or the parallel annotation of multiple compounds in multiple files. A graphical user interface as well as command line functions will assist in assessing the quality of annotation and update fitting parameters until a satisfactory result is obtained.
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.
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.
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 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.
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.