This package provides functions for financial analysis and financial modeling, including batch graphs generation, beta calculation, descriptive statistics, annuity calculation, bond pricing and financial data download.

Log-ratio Lasso regression for continuous, binary, and survival outcomes with (longitudinal) compositional features. See Fei and others (2024) <doi:10.1016/j.crmeth.2024.100899>.

Package for haplotype-based genotype simulations. Haplotypes are generated such that their allele frequencies and linkage disequilibrium coefficients match those estimated from an input data set.

Assists in generating binary clustered data, estimates of Intracluster Correlation coefficient (ICC) for binary response in 16 different methods, and 5 different types of confidence intervals.

This package provides methods for fitting log-link GLMs and GAMs to binomial data, including EM-type algorithms with more stable convergence properties than standard methods.

This package provides methods of selecting one from many numeric predictors for a regression model, to ensure that the additional predictor has the maximum effect size.

Find dark genes. These genes are often disregarded due to no detected mutation or differential expression, but are important in coordinating the functionality in cancer networks.

Features unstructured, structured and reverse geocoding using the photon geocoding API <https://photon.komoot.io/>. Facilitates the setup of local photon instances to enable offline geocoding.

This package provides functions are primarily functions for systems of ordinary differential equations, difference equations, and eigenanalysis and projection of demographic matrices; data are for examples.

Compute various quantitative genetics parameters from a Generalised Linear Mixed Model (GLMM) estimates. Especially, it yields the observed phenotypic mean, phenotypic variance and additive genetic variance.

Uses statistical network modeling to understand the co-expression relationships among genes and to construct sparse gene co-expression networks from single-cell gene expression data.

Develops a framework for fisheries stock assessment simulation testing with Stock Synthesis (SS) as described in Anderson et al. (2014) <doi:10.1371/journal.pone.0092725>.

Converts the floor speeches of Uruguayan legislators, extracted from the parliamentary minutes, to tidy data.frame where each observation is the intervention of a single legislator.

Construct subtests from a pool of items by using ant-colony-optimization, genetic algorithms, brute force, or random sampling. Schultze (2017) <doi:10.17169/refubium-622>.

Create HTML tables of descriptive statistics, as one would expect to see as the first table (i.e. "Table 1") in a medical/epidemiological journal article.

The companion package that provides all the datasets used in the book "Data Integration, Manipulation and Visualization of Phylogenetic Trees" by Guangchuang Yu (2022, ISBN:9781032233574).

This package provides functions for statistical analysis, prediction and control of time series based mainly on Akaike and Nakagawa (1988) <ISBN 978-90-277-2786-2>.

Error variance estimation in ultrahigh dimensional datasets with four different methods, viz. Refitted cross validation, k-fold refitted cross validation, Bootstrap-refitted cross validation, Ensemble method.

Calculates the volume under the ROC surface and its (co)variance for ordered multi-class ROC analysis as well as certain bivariate ordinal measures of association.

Package that implements the COSNet classification algorithm. The algorithm predicts node labels in partially labeled graphs where few positives are available for the class being predicted.

Trendy implements segmented (or breakpoint) regression models to estimate breakpoints which represent changes in expression for each feature/gene in high throughput data with ordered conditions.

This package provides routines for parsing Affymetrix data files based upon file format information. The primary focus is on accessing the CEL and CDF file formats.

The parody package provides routines for univariate and multivariate outlier detection with a focus on parametric methods, but support for some methods based on resistant statistics.

randfold computes the probability that, for a given sequence, the Minimum Free Energy (MFE) of the secondary structure is different from MFE computed with random sequences.