This package provides functions to access historical and real-time national hydrometric data from Water Survey of Canada data sources and then applies tidy data principles.

The general principle relies on calculating the cumulative signal of nascent RNA sequencing over the gene body of any given gene or transcription unit. tepr can identify transcription attenuation sites by comparing profile to a null model which assumes uniform read density over the entirety of the transcription unit. It can also identify increased or diminished transcription attenuation by comparing two conditions. Besides rigorous statistical testing and high sensitivity, a major feature of tepr is its ability to provide the elongation pattern of each individual gene, including the position of the main attenuation point when such a phenomenon occurs. Using tepr', users can visualize and refine genome-wide aggregated analyses of elongation patterns to robustly identify effects specific to subsets of genes. These metrics are suitable for internal comparisons (between genes in each condition) and for studying elongation of the same gene in different conditions or comparing it to a perfect theoretical uniform elongation.

Uses thresholded partial least squares algorithm to create a regression or classification model. For more information, see Lee, Bradlow, and Kable <doi:10.1016/j.crmeth.2022.100227>.

This package provides functions to combine data.frames in ways that require additional effort in base R, and to add metadata (id, title, ...) that can be used for printing and xlsx export. The Tatoo_report class is provided as a convenient helper to write several such tables to a workbook, one table per worksheet. Tatoo is built on top of openxlsx', but intimate knowledge of that package is not required to use tatoo.

It creates an invisible layer that allow to see the Seurat object as tibble and interact seamlessly with the tidyverse.

This package provides a unified estimation procedure for the analysis of right censored data using linear transformation models. An introduction can be found in Jie Zhou et al. (2022) <doi:10.18637/jss.v101.i09>.

This package provides a tidy-style interface for applying differential privacy to data frames. Provides pipe-friendly functions to add calibrated noise, compute private statistics, and track privacy budgets using the epsilon-delta differential privacy framework. Implements the Laplace mechanism (Dwork et al. 2006 <doi:10.1007/11681878_14>) and the Gaussian mechanism for achieving differential privacy as described in Dwork and Roth (2014) <doi:10.1561/0400000042>.

This package provides tools to calculate trait probability density functions (TPD) at any scale (e.g. populations, species, communities). TPD functions are used to compute several indices of functional diversity, as well as its partition across scales. These indices constitute a unified framework that incorporates the underlying probabilistic nature of trait distributions into uni- or multidimensional functional trait-based studies. See Carmona et al. (2016) <doi:10.1016/j.tree.2016.02.003> for further information.

Calculates the robust Taba linear, Taba rank (monotonic), TabWil, and TabWil rank correlations. Test statistics as well as one sided or two sided p-values are provided for all correlations. Multiple correlations and p-values can be calculated simultaneously across multiple variables. In addition, users will have the option to use the partial, semipartial, and generalized partial correlations; where the partial and semipartial correlations use linear, logistic, or Poisson regression to modify the specified variable.

Univariate time series operations that follow an opinionated design. The main principle of transx is to keep the number of observations the same. Operations that reduce this number have to fill the observations gap.

This package provides datasets in a format that can be easily consumed by torch dataloaders'. Handles data downloading from multiple sources, caching and pre-processing so users can focus only on their model implementations.

Find the optimal decision rules (AKA progression criteria) and sample size for clinical trials with three (stop/pause/go) outcomes. Both binary and continuous endpoints can be accommodated, as can cases where an adjustment is planned following a pause outcome. For more details see Wilson et al. (2024) <doi:10.1186/s12874-024-02351-x>.

Detection of outliers in time series following the Chen and Liu (1993) <DOI:10.2307/2290724> procedure. Innovational outliers, additive outliers, level shifts, temporary changes and seasonal level shifts are considered.

This package produces weighted cross-tabulation tables for one or more outcome variables across one or more breakdown variables, and exports them directly to Excel'. For each outcome-by-breakdown combination, the package creates a weighted percentage table and a corresponding unweighted count table, with transparent handling of missing values and light, readable formatting. Designed to support social survey analysis workflows that require large sets of consistent, publication-ready tables.

This package provides various commonly-used response time trimming methods, including the recursive / moving-criterion methods reported by Van Selst and Jolicoeur (1994). By passing trimming functions raw data files, the package will return trimmed data ready for inferential testing.

This package provides a graphics output device for R that records plots in a LaTeX-friendly format. The device transforms plotting commands issued by R functions into LaTeX code blocks. When included in a LaTeX document, these blocks are interpreted with the help of TikZ'---a graphics package for TeX and friends written by Till Tantau. Using the tikzDevice', the text of R plots can contain LaTeX commands such as mathematical formula. The device also allows arbitrary LaTeX code to be inserted into the output stream.

In Cox's proportional hazard model, covariates are modeled as linear function and may not be flexible. This package implements additive trend filtering Cox proportional hazards model as proposed in Jiacheng Wu & Daniela Witten (2019) "Flexible and Interpretable Models for Survival Data", Journal of Computational and Graphical Statistics, <DOI:10.1080/10618600.2019.1592758>. The fitted functions are piecewise polynomial with adaptively chosen knots.

User-friendly analysis of hierarchical multinomial processing tree (MPT) models that are often used in cognitive psychology. Implements the latent-trait MPT approach (Klauer, 2010) <DOI:10.1007/s11336-009-9141-0> and the beta-MPT approach (Smith & Batchelder, 2010) <DOI:10.1016/j.jmp.2009.06.007> to model heterogeneity of participants. MPT models are conveniently specified by an .eqn-file as used by other MPT software and data are provided by a .csv-file or directly in R. Models are either fitted by calling JAGS or by an MPT-tailored Gibbs sampler in C++ (only for nonhierarchical and beta MPT models). Provides tests of heterogeneity and MPT-tailored summaries and plotting functions. A detailed documentation is available in Heck, Arnold, & Arnold (2018) <DOI:10.3758/s13428-017-0869-7> and a tutorial on MPT modeling can be found in Schmidt, Erdfelder, & Heck (2023) <DOI:10.1037/met0000561>.

Models the direction of the maximum horizontal stress using relative plate motion parameters. Statistical algorithms to evaluate the modeling results compared with the observed data. Provides plots to visualize the results. Methods described in Stephan et al. (2023) <doi:10.1038/s41598-023-42433-2> and Wdowinski (1998) <doi:10.1016/S0079-1946(98)00091-3>.

Multiple flavors of the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model with a large choice of conditional distributions. Methods for specification, estimation, prediction, filtering, simulation, statistical testing and more. Represents a partial re-write and re-think of rugarch', making use of automatic differentiation for estimation.

Helper functions for processing REDCap data in R. REDCap is a web-enabled application for building and managing surveys and databases developed at Vanderbilt University.

Parsing (R)Markdown files with numerous regular expressions can be fraught with peril, but it does not have to be this way. Converting (R)Markdown files to XML using the commonmark package allows in-memory editing via of markdown elements via XPath through the extensible R6 class called yarn'. These modified XML representations can be written to (R)Markdown documents via an xslt stylesheet which implements an extended version of GitHub'-flavoured markdown so that you can tinker to your hearts content.

This package provides functions for multivariate analysis with compositional data. Includes a function for doing compositional canonical correlation analysis. This analysis requires two data matrices of compositions, which can be adequately transformed and used as entries in a specialized program for canonical correlation analysis, that is able to deal with singular covariance matrices. The methodology is described in Graffelman et al. (2017) <doi:10.1101/144584>. Functions for log-ratio principal component analysis with condition number computations and log-ratio discriminant analysis have been added to the package.

Agglomerative hierarchical clustering with a bespoke distance measure based on medication similarities in the Anatomical Therapeutic Chemical Classification System, medication timing and medication amount or dosage. Tools for summarizing, illustrating and manipulating the cluster objects are also available.