To assess a summary survival curve from survival probabilities and number of at-risk patients collected at various points in time in various studies, and to test the between-strata heterogeneity.

Flexible optimizer with numerous input specifications for detailed parameterisation. Designed for complex loss functions with state and parameter space constraints. Visualization tools for validation and analysis of the convergence are included.

This package provides nonparametric Steinian shrinkage estimators of the covariance matrix that are suitable in high dimensional settings, that is when the number of variables is larger than the sample size.

This package provides functions to estimate the proportion of treatment effect explained by the surrogate marker using a Bayesian Model Averaging approach. Duan and Parast (2023) <doi:10.1002/sim.9986>.

Variance approximations for the Horvitz-Thompson total estimator in Unequal Probability Sampling using only first-order inclusion probabilities. See Matei and Tillé (2005) and Haziza, Mecatti and Rao (2008) for details.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was Barley1\_probe\_tab.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was Chicken\_probe\_tab.

Experimental data with Affymetrix E. coli chips, as reported in She-pin Hung, Pierre Baldi, and G. Wesley Hatfield, J. Biol. Chem., Vol. 277, Issue 43, 40309-40323, October 25, 2002.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was MOE430B\_probe\_tab.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was MOE430A\_probe\_tab.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was Porcine\_probe\_tab.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was Soybean\_probe\_tab.

This package provides tools to convert the output of utils::getParseData() to an XML tree, that one can search via XPath, and is easier to manipulate in general.

Convert a logical vector or a vector of p-values or a correlation, difference, or distance matrix into a display identifying the pairs for which the differences were not significantly different.

This package uses the node library is-my-json-valid or ajv to validate JSON against a JSON schema. Drafts 04, 06 and 07 of JSON schema are supported.

This module provides line editing support via the Readline library for GNU Guile. Use the (ice-9 readline) module and call its activate-readline procedure to enable it.

This Common Lisp library focuses on the small set of basic color manipulations (lightening, compliments, etc.) you might use to generate a color palette for a GUI or web page.

rfc3986 is a Python implementation of RFC 3986 including validation and authority parsing. This module also supports RFC 6874 which adds support for zone identifiers to IPv6 addresses.

This package provides functions to compute the distribution function of quadratic forms in normal variables using Imhof's method, Davies's algorithm, Farebrother's algorithm or Liu et al.'s algorithm.

This package implements piecewise structural equation modeling from a single list of structural equations, with new methods for non-linear, latent, and composite variables, standardized coefficients, query-based prediction and indirect effects.

An R interface to the Base dos Dados API <https:basedosdados.github.io/mais/py_reference_api/>). Authenticate your project, query our tables, save data to disk and memory, all from R.

New approaches to parallel coordinates plots for multivariate data visualization, including applications to clustering, outlier hunting and regression diagnostics. Includes general functions for multivariate nonparametric density and regression estimation, using parallel computation.

An implementation of a new Gini covariance and correlation to measure dependence between a categorical and numerical variables. Dang, X., Nguyen, D., Chen, Y. and Zhang, J., (2018) <arXiv:1809.09793>.

Allows to create modular, reusable HTML forms which can be embedded in your shiny app with minimal effort. Features include conditional code execution on form submission, automatic input validation and input tooltips.