This package provides a dependency-free collection of simple functions for cleaning rectangular data. This package allows to detect, count and replace values or discard rows/columns using a predicate function. In addition, it provides tools to check conditions and return informative error messages.

Computes exact bounds of Spearman's footrule in the presence of missing data, and performs independence test based on the bounds with controlled Type I error regardless of the values of missing data. Suitable only for distinct, univariate data where no ties is allowed.

Fork-safe, raw access to the Amazon Web Services ('AWS') SDK via the boto3 Python module, and convenient helper functions to query the Simple Storage Service ('S3') and Key Management Service ('KMS'), partial support for IAM', the Systems Manager Parameter Store and Secrets Manager'.

Calculate the predictive discrete Fourier transform, complete discrete Fourier transform, complete periodogram, and tapered complete periodogram. This algorithm is based on the preprint "Spectral methods for small sample time series: A complete periodogram approach" (2020) by Sourav Das, Suhasini Subba Rao, and Junho Yang.

This package provides functions for generating, simulating, and visualizing expected durations and marginal changes in duration from the Cox proportional hazards model as described in Kropko and Harden (2017) <doi:10.1017/S000712341700045X> and Harden and Kropko (2018) <doi:10.1017/psrm.2018.19>.

Function to test spatial segregation and association based in contingency table analysis of nearest neighbour counts following Dixon (2002) <doi:10.1080/11956860.2002.11682700>. Some Fortran code has been included to the original dixon2002() function of the ecespa package to improve speed.

This package provides a `.` object which can be used for unpacking assignments. For example, `.[rows, columns] <- dim(cars)` could be used to pull the number of rows and number of columns from `dim(cars)` into individual variables `rows` and `columns` in a single step.

This package provides a flexible permutation framework for making inference such as point estimation, confidence intervals or hypothesis testing, on any kind of data, be it univariate, multivariate, or more complex such as network-valued data, topological data, functional data or density-valued data.

Parse and create Darwin Core (<http://rs.tdwg.org/dwc/>) Simple and Archives. Functionality includes reading and parsing all the files in a Darwin Core Archive, including the datasets and metadata; read and parse simple Darwin Core files; and validation of Darwin Core Archives.

This package provides functions for importing, creating, editing and exporting FSK files <https://foodrisklabs.bfr.bund.de/fskx-food-safety-knowledge-exchange-format/> using the R programming environment. Furthermore, it enables users to run simulations contained in the FSK files and visualize the results.

This package contains functions to fetch data from various data sources. The user first creates a catalog of objects from a data source, then fetches data from the catalog. The package provides an easy way to access data from many different types of sources.

Set of routines for influence diagnostics by using case-deletion in ordinary least squares, ridge estimation [Walker and Birch (1988). <doi:10.1080/00401706.1988.10488370>] and least absolute deviations (LAD) regression [Sun and Wei (2004). <doi:10.1016/j.spl.2003.08.018>].

Temporary and permanent message queues for R. Built on top of SQLite databases. SQLite provides locking, and makes it possible to detect crashed consumers. Crashed jobs can be automatically marked as "failed", or put in the queue again, potentially a limited number of times.

This is an implementation of the partial profile score feature selection (PPSFS) approach to generalized linear (interaction) models. The PPSFS is highly scalable even for ultra-high-dimensional feature space. See the paper by Xu, Luo and Chen (2021, <doi:10.4310/21-SII706>).

Given a SpatialPolygonsDataFrame and a set of populations for each polygon, compute a population density estimate based on Tobler's pycnophylactic interpolation algorithm. The result is a SpatialGridDataFrame. Methods are described in Tobler Waldo R. (1979) <doi:10.1080/01621459.1979.10481647>.

Full pattern summation of X-ray powder diffraction data as described in Chipera and Bish (2002) <doi:10.1107/S0021889802017405> and Butler and Hillier (2021) <doi:10.1016/j.cageo.2020.104662>. Derives quantitative estimates of crystalline and amorphous phase concentrations in complex mixtures.

This package provides tools for retrieving, organizing, and analyzing environmental data from the System Wide Monitoring Program of the National Estuarine Research Reserve System <https://cdmo.baruch.sc.edu/>. These tools address common challenges associated with continuous time series data for environmental decision making.

Handles both vector and matrices, using a flexible S4 class for automatic differentiation. The method used is forward automatic differentiation. Many functions and methods have been defined, so that in most cases, functions written without automatic differentiation in mind can be used without change.

Regularized version of partial least square approaches providing sparse, group, and sparse group versions of partial least square regression models (Liquet, B., Lafaye de Micheaux, P., Hejblum B., Thiebaut, R. (2016) <doi:10.1093/bioinformatics/btv535>). Version of PLS Discriminant analysis is also provided.

Accompanies the book Rainer Schlittgen and Cristina Sattarhoff (2020) <https://www.degruyter.com/view/title/575978> "Angewandte Zeitreihenanalyse mit R, 4. Auflage" . The package contains the time series and functions used therein. It was developed over many years teaching courses about time series analysis.

This package provides a simple type annotation for R that is usable in scripts, in the R console and in packages. It is intended as a convention to allow other packages to use the type information to provide error checking, automatic documentation or optimizations.

"Methylation-Aware Genotype Association in R" (MAGAR) computes methQTL from DNA methylation and genotyping data from matched samples. MAGAR uses a linear modeling stragety to call CpGs/SNPs that are methQTLs. MAGAR accounts for the local correlation structure of CpGs.

This package is used for the identification and validation of sequence motifs. It makes use of STAMP for comparing a set of motifs to a given database (e.g. JASPAR). It can also be used to visualize motifs, motif distributions, modules and filter motifs.

This package provides functions to compute insolation on tilted surfaces, computes atmospheric transmittance and related parameters such as: Earth radius vector, declination, sunset and sunrise, daylength, equation of time, vector in the direction of the sun, vector normal to surface, and some atmospheric physics.