Package to analyze the clinical utility of a biomarker. It provides the clinical utility curve, clinical utility table, efficacy of a biomarker, clinical efficacy curve and tests to compare efficacy between markers.

Can be useful for finding associations among different positions in a position-wise aligned sequence dataset. The approach adopted for finding associations among positions is based on the latent multivariate normal distribution.

This package contains one main function deduped() which speeds up slow, vectorized functions by only performing computations on the unique values of the input and expanding the results at the end.

Build donut/pie charts with ggplot2 layer by layer, exploiting the advantages of polar symmetry. Leverage layouts to distribute labels effectively. Connect labels to donut segments using pins. Streamline annotation and highlighting.

Work within the dplyr workflow to add random variates to your data frame. Variates can be added at any level of an existing column. Also, bounds can be specified for simulated variates.

This cointegration based Time Delay Neural Network Model hybrid model allows the researcher to make use of the information extracted by the cointegrating vector as an input in the neural network model.

This package contains a collection of examples of evidence factors in observational studies from the book Replication and Evidence Factors in Observational Studies by Paul R. Rosenbaum (2021) <doi:10.1201/9781003039648>.

This SVG elements generator can easily generate SVG elements such as rect, line, circle, ellipse, polygon, polyline, text and group. Also, it can combine and output SVG elements into a SVG file.

Obtain Formula 1 data via the Jolpica API <https://jolpi.ca> and the unofficial API <https://www.formula1.com/en/timing/f1-live> via the fastf1 Python library <https://docs.fastf1.dev/>.

Finds the critical sample size ("critical point of stability") for a correlation to stabilize in Schoenbrodt and Perugini's definition of sequential stability (see <doi:10.1016/j.jrp.2013.05.009>).

This package provides ggplot2 geoms that allow groups of data points to be outlined or highlighted for emphasis. This is particularly useful when working with dense datasets that are prone to overplotting.

Various functions and a Shiny app to enrich the results of Multiple Correspondence Analysis with interpretive axes and planes (see Moschidis, Markos, and Thanopoulos, 2022; <doi:10.1108/ACI-07-2022-0191>).

Multivariate Expectation-Maximization (EM) based imputation framework that offers several different algorithms. These include regularisation methods like Lasso and Ridge regression, tree-based models and dimensionality reduction methods like PCA and PLS.

This package contains data sets, programmes and illustrations discussed in the book, "Introduction to Probability, Statistics and R: Foundations for Data-Based Sciences." Sahu (2024, isbn:9783031378645) describes the methods in detail.

This package provides a graph proposed by Rosenbaum is useful for checking some properties of various sorts of latent scale, this program generates commands to obtain the graph using dot from graphviz'.

Fit multi-level models with possibly correlated random effects using Markov Chain Monte Carlo simulation. Such models allow smoothing over space and time and are useful in, for example, small area estimation.

This package provides a simple n-gram (contiguous sequences of n items from a given sequence of text) tokenizer to be used with the tm package with no rJava'/'RWeka dependency.

Given a certain coverage level, obtains simultaneous confidence bands for the survival and cumulative hazard functions such that the area between is minimized. Produces an approximate solution based on local time arguments.

Estimates win ratio or Mann-Whitney parameter for two group comparisons using ordered composite endpoints with right censoring as described in Follmann, Fay, Hamasaki, and Evans (2020)<doi:10.1002/sim.7890>.

This wrapper houses PathLit API endpoints for R. The usage of these endpoints require the use of an API key which can be obtained at <https://www.pathlit.io/docs/cli/>.

Perform joint segmentation on two signal dimensions derived from total read depth (intensity) and allele specific read depth (intensity) for whole genome sequencing (WGS), whole exome sequencing (WES) and SNP array data.

Routines for computing different types of linear estimators, based on instrumental variables (IVs), including the semi-parametric Stein-like (SPS) estimator, originally introduced by Judge and Mittelhammer (2004) <DOI:10.1198/016214504000000430>.

Computes likelihood ratio test (LRT) p-values for free parameters in a structural equation model. Currently supports models fitted by the lavaan package by Rosseel (2012) <doi:10.18637/jss.v048.i02>.

Create scaled ggplot representations of playing surfaces. Playing surfaces are drawn pursuant to rule-book specifications. This package should be used as a baseline plot for displaying any type of tracking data.