An inverse probability of censoring weighted (IPCW) targeted maximum likelihood estimator (TMLE) for evaluating a marginal point treatment effect from data where some variables were collected on only a subset of participants using a two-stage design (or marginal mean outcome for a single arm study). A TMLE for conditional parameters defined by a marginal structural model (MSM) is also available.

Temporal disaggregation methods are used to disaggregate and interpolate a low frequency time series to a higher frequency series, where either the sum, the mean, the first or the last value of the resulting high frequency series is consistent with the low frequency series. Temporal disaggregation can be performed with or without one or more high frequency indicator series. Contains the methods of Chow-Lin, Santos-Silva-Cardoso, Fernandez, Litterman, Denton and Denton-Cholette, summarized in Sax and Steiner (2013) <doi:10.32614/RJ-2013-028>. Supports most R time series classes.

Performing the hypothesis tests for the two sample problem based on order statistics and power comparisons. Calculate the test statistic, density, distribution function, quantile function, random number generation and others.

To make it easy to generate random numbers based upon the underlying stats distribution functions. All data is returned in a tidy and structured format making working with the data simple and straight forward. Given that the data is returned in a tidy tibble it lends itself to working with the rest of the tidyverse'.

This package provides a collection of functions for data analysis with two-by-two contingency tables. The package provides tools to compute measures of effect (odds ratio, risk ratio, and risk difference), calculate impact numbers and attributable fractions, and perform hypothesis testing. Statistical analysis methods are oriented towards epidemiological investigation of relationships between exposures and outcomes.

This package provides a tidy workflow for generating, estimating, reporting, and plotting structural equation models using lavaan', OpenMx', or Mplus'. Throughout this workflow, elements of syntax, results, and graphs are represented as tidy data, making them easy to customize. Includes functionality to estimate latent class analyses, and to plot dagitty and igraph objects.

Easy install and load key packages from the tesselle suite in a single step. The tesselle suite is a collection of packages for research and teaching in archaeology. These packages focus on quantitative analysis methods developed for archaeology. The tesselle packages are designed to work seamlessly together and to complement general-purpose and other specialized statistical packages. These packages can be used to explore and analyze common data types in archaeology: count data, compositional data and chronological data. Learn more about tesselle at <https://www.tesselle.org>.

This package provides a new measure of similarity between a pair of mass spectrometry (MS) experiments, called truncated rank correlation (TRC). To provide a robust metric of similarity in noisy high-dimensional data, TRC uses truncated top ranks (or top m-ranks) for calculating correlation. Truncated rank correlation as a robust measure of test-retest reliability in mass spectrometry data. For more details see Lim et al. (2019) <doi:10.1515/sagmb-2018-0056>.

The goal of this package will be to provide a simple interface for automatic machine learning that fits the tidymodels framework. The intention is to work for regression and classification problems with a simple verb framework.

An aid for text mining in R, with a syntax that should be familiar to experienced R users. Provides a wrapper for several topic models that take similarly-formatted input and give similarly-formatted output. Has additional functionality for analyzing and diagnostics for topic models.

Extension of funHDDC Schmutz et al. (2018) <doi:10.1007/s00180-020-00958-4> for cases including outliers by fitting t-distributions for robust groups. TFunHDDC can cluster univariate or multivariate data produced by the fda package for data using a b-splines or Fourier basis.

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>.

Allow to compute and visualise convective parameters commonly used in the operational prediction of severe convective storms. Core algorithm is based on a highly optimized C++ code linked into R via Rcpp'. Highly efficient engine allows to derive thermodynamic and kinematic parameters from large numerical datasets such as reanalyses or operational Numerical Weather Prediction models in a reasonable amount of time. Package has been developed since 2017 by research meteorologists specializing in severe thunderstorms. The most relevant methods used in the package based on the following publications Stipanuk (1973) <https://apps.dtic.mil/sti/pdfs/AD0769739.pdf>, McCann et al. (1994) <doi:10.1175/1520-0434(1994)009%3C0532:WNIFFM%3E2.0.CO;2>, Bunkers et al. (2000) <doi:10.1175/1520-0434(2000)015%3C0061:PSMUAN%3E2.0.CO;2>, Corfidi et al. (2003) <doi:10.1175/1520-0434(2003)018%3C0997:CPAMPF%3E2.0.CO;2>, Showalter (1953) <doi:10.1175/1520-0477-34.6.250>, Coffer et al. (2019) <doi:10.1175/WAF-D-19-0115.1>, Gropp and Davenport (2019) <doi:10.1175/WAF-D-17-0150.1>, Czernecki et al. (2019) <doi:10.1016/j.atmosres.2019.05.010>, Taszarek et al. (2020) <doi:10.1175/JCLI-D-20-0346.1>, Sherburn and Parker (2014) <doi:10.1175/WAF-D-13-00041.1>, Romanic et al. (2022) <doi:10.1016/j.wace.2022.100474>.

This package provides a collection of functions used to format taxonomic names in Markdown documents. Those functions work with data structured according to Alvarez and Luebert (2018) <doi:10.3897/bdj.6.e23635>.

This package implements a decomposition of the two-way fixed effects instrumental variable estimator into all possible Wald difference-in-differences estimators. Provides functions to summarize the contribution of different cohort comparisons to the overall two-way fixed effects instrumental variable estimate, with or without controls. The method is described in Miyaji (2024) <doi:10.48550/arXiv.2405.16467>.

Converting text to numerical features requires specifically created procedures, which are implemented as steps according to the recipes package. These steps allows for tokenization, filtering, counting (tf and tfidf) and feature hashing.

This package provides new layer functions to tmap for creating various types of cartograms. A cartogram is a type of thematic map in which geographic areas are resized or distorted based on a quantitative variable, such as population. The goal is to make the area sizes proportional to the selected variable while preserving geographic positions as much as possible.

This package provides two classes extending data.table class. Simple tableList class wraps data.table and any additional structures together. More complex tableMatrix class combines data.table and matrix'. See <http://github.com/InferenceTechnologies/tableMatrix> for more information and examples.

Parse XML documents from the Open Access subset of Europe PubMed Central <https://europepmc.org> including section paragraphs, tables, captions and references.

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

Does nothing useful, but perhaps does that nothing in an entertaining or informative fashion.

We focus on the diagnostic ability assessment of medical tests when the outcome of interest is the status (alive or dead) of the subjects at a certain time-point t. This binary status is determined by right-censored times to event and it is unknown for those subjects censored before t. Here we provide three methods (unknown status exclusion, imputation of censored times and using time-dependent ROC curves) to evaluate the diagnostic ability of binary and continuous tests in this context. Two references for the methods used here are Skaltsa et al. (2010) <doi:10.1002/bimj.200900294> and Heagerty et al. (2000) <doi:10.1111/j.0006-341x.2000.00337.x>.

This package provides functions to generate stop-word lists in 110 languages, in a way consistent across all the languages supported. The generated lists are based on the morphological tagset from the Universal Dependencies.

Allows users to quickly load multiple patients electrocardiographic (ECG) data at once and conduct relevant time analysis of heart rate variability (HRV) without manual edits from a physician or data cleaning specialist. The package provides the unique ability to iteratively filter, plot, and store time analysis results in a data frame while writing plots to a predefined folder. This streamlines the workflow for HRV analysis across multiple datasets. Methods are based on Rodrà guez-Liñares et al. (2011) <doi:10.1016/j.cmpb.2010.05.012>. Examples of applications using this package include Kwon et al. (2022) <doi:10.1007/s10286-022-00865-2> and Lawrence et al. (2023) <doi:10.1016/j.autneu.2022.103056>.