Provides a unified interface to large language models across multiple
  providers. Supports text generation, structured output with optional JSON
  Schema validation, and embeddings. Includes tidyverse-friendly helpers,
  chat session, consistent error handling, and parallel batch tools.

A 'shiny' application to automate forward and back survey translation 
    with optional reconciliation using large language models (LLMs). It follows 
    the TRAPD (Translation, Review, Adjudication, Pretesting, Documentation) 
    framework and ISPOR (International Society for Pharmacoeconomics and 
    Outcomes Research) recommendations. See Harkness et al. (2010) 
    <doi:10.1002/9780470609927.ch7> and Wild et al. (2005) 
    <doi:10.1111/j.1524-4733.2005.04054.x>.

Density, distribution function, quantile function and random generation for the L-Logistic distribution with parameters m and phi. The parameter m is the median of the distribution.

Originally design to characterise Aqueous Two Phase Systems, LLSR provide a simple way to analyse experimental data and obtain phase diagram parameters, among other properties, systematically. The package will include (every other update) new functions in order to comprise useful tools in liquid-liquid extraction research.

Adds standardized regression coefficients to objects created by 'lm'. Also extends the S3 methods 'print', 'summary' and 'coef' with additional boolean argument 'standardized' and provides 'xtable'-support.

Exact significance tests for a changepoint in linear or multiple linear regression.  
  Confidence regions with exact coverage probabilities for the changepoint.  Based on 
  Knowles, Siegmund and Zhang (1991) <doi:10.1093/biomet/78.1.15>.

Set of tools for mapping of categorical response variables based on principal component analysis (pca) and multidimensional unfolding (mdu).

Various efficient and robust bootstrap methods are implemented for 
    linear models with least squares estimation.  Functions within this package 
    allow users to create bootstrap sampling distributions for model parameters, 
    test hypotheses about parameters, and visualize the bootstrap sampling or null 
    distributions.  Methods implemented for linear models include the wild bootstrap by 
    Wu (1986) <doi:10.1214/aos/1176350142>, the residual and paired bootstraps by
    Efron (1979, ISBN:978-1-4612-4380-9), the delete-1 jackknife by 
    Quenouille (1956) <doi:10.2307/2332914>, and the Bayesian bootstrap by 
    Rubin (1981) <doi:10.1214/aos/1176345338>.