This package produces forest plots using ggplot2 from models produced by functions such as stats::lm(), stats::glm() and survival::coxph().

Easily create overlapping grammar of graphics plots for scientific data visualization. This style of plotting is particularly common in climatology and oceanography research communities.

Simulation tool to facilitate determination of required sample size to achieve category saturation for studies using multiple repertory grids in conjunction with content analysis.

Flowcharts can be a useful way to visualise complex processes. This package uses the layered grammar of graphics of ggplot2 to create simple flowcharts.

Trace plots and convergence diagnostics for Markov Chain Monte Carlo (MCMC) algorithms on highly multivariate or unordered spaces. Methods outlined in a forthcoming paper.

Run quality checks on data sets using the same checks that are conducted on the ICES Data Submission Utility (DATSU) <https://datsu.ices.dk>.

Helper functions for producing reports in Psychology (Reproducible Research). Provides required formatted strings (APA style) for use in Knitr'/'Latex integration within *.Rnw files.

This package creates simulated data from structural equation models with standardized loading. Data generation methods are described in Schneider (2013) <doi:10.1177/0734282913478046>.

This package creates a lightweight way to add markdown helpfiles to Shiny apps, using modal dialog boxes, with no need to observe each help button separately.

This package contains functionality for performing the following methods of p-value aggregation: Fisher's method, the Lancaster method (weighted Fisher's method), and Sidak correction.

This library provides a Rust binding to the original implementation of webview, a tiny cross-platform library to render web-based GUIs as desktop applications.

The trimmed k-means clustering method by Cuesta-Albertos, Gordaliza and Matran (1997). This optimizes the k-means criterion under trimming a portion of the points.

This package provides a package to suggest the number of mutational signatures in a collection of somatic mutations using calculating the cross-validated perplexity score.

This data package contains a subset of the Bodenmiller et al, Nat Biotech 2012 dataset for testing single cell, high dimensional analysis and visualization methods.

This data package contains monthly climate data in Germany, it can be used for heating and cooling calculations (external temperature, heating / cooling days, solar radiation).

Fit a mixture of Discrete Laplace distributions using plain numerical optimisation. This package has similar applications as the disclapmix package that uses an EM algorithm.

Generates an RMarkdown data report with two components: a summary of an input dataset and a diff of the dataset relative to an old version.

Bayesian Model Averaging to create probabilistic forecasts from ensemble forecasts and weather observations <https://stat.uw.edu/sites/default/files/files/reports/2007/tr516.pdf>.

Fit and sample from the ensemble model described in Spence et al (2018): "A general framework for combining ecosystem models"<doi:10.1111/faf.12310>.

This package provides tools for analyzing remote sensing forest data, including functions for detecting treetops from canopy models, outlining tree crowns, and calculating textural metrics.

This package implements imputation methods using EM and Data Augmentation for multinomial data following the work of Schafer 1997 <ISBN: 978-0-412-04061-0>.

Distributional regression under stochastic order restrictions for numeric and binary response variables and partially ordered covariates. See Henzi, Ziegel, Gneiting (2020) <arXiv:1909.03725>.

This package provides tools for mapping International Classification of Diseases codes to comorbidity, enabling the identification and analysis of various medical conditions within healthcare data.

Miscellaneous functions commonly used by LuLab. This package aims to help more researchers on epidemiology to perform data management and visualization more efficiently.