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If you'd like to join our channel search send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.
Calculates landscape metrics for categorical landscape patterns in a tidy workflow. landscapemetrics reimplements the most common metrics from FRAGSTATS (<https://www.fragstats.org/>) and new ones from the current literature on landscape metrics. This package supports terra SpatRaster objects as input arguments. It further provides utility functions to visualize patches, select metrics and building blocks to develop new metrics.
Build complex LaTeX mathematical expressions using intuitive R functions. Replace error-prone LaTeX syntax with readable, modular functions that make mathematical typesetting straightforward and maintainable.
This package provides a collection of hypothesis tests and confidence intervals based on the likelihood ratio <https://en.wikipedia.org/wiki/Likelihood-ratio_test>.
Parse various reflectance/transmittance/absorbance spectra file formats to extract spectral data and metadata, as described in Gruson, White & Maia (2019) <doi:10.21105/joss.01857>. Among other formats, it can import files from Avantes <https://www.avantes.com/>, CRAIC <https://www.microspectra.com/>, and OceanOptics'/'OceanInsight <https://www.oceanoptics.com/> brands.
This package provides functions that allow for convenient working with vector space models of semantics/distributional semantic models/word embeddings. Originally built for LSA models (hence the name), but can be used for all such vector-based models. For actually building a vector semantic space, use the package lsa or other specialized software. Downloadable semantic spaces can be found at <https://sites.google.com/site/fritzgntr/software-resources>.
Render LimeSurvey .lss survey exports as multilingual questionnaire documents in Word ('.docx') or PDF, displaying up to four languages side by side with localized chrome in English, French, German, Spanish and Italian. Includes a rule-based automated audit that flags missing translations, forward filter references, duplicate codes, array-scale inconsistencies and orphan structural references. Designed for anyone working with a LimeSurvey survey: researchers, methodologists, ethics committees, translators and reviewers. Processing is fully local: the source file is the only input and no questionnaire content is uploaded to a third-party service.
Perform pairwise likelihood inference in latent autoregressive count models. See Pedeli and Varin (2020) for details.
Computational routines for estimating local Gaussian parameters. Local Gaussian parameters are useful for characterizing and testing for non-linear dependence within bivariate data. See e.g. Tjostheim and Hufthammer, Local Gaussian correlation: A new measure of dependence, Journal of Econometrics, 2013, Volume 172 (1), pages 33-48 <DOI:10.1016/j.jeconom.2012.08.001>.
An RStudio addin that integrates large language model (LLM) assistance directly into the code-editing workflow. Features include: (1) generate R code from inline comments; (2) obtain LLM-assisted fixes for console errors; (3) insert plain-English explanations of selected code blocks; (4) a multi-turn Chat Panel with session-context awareness (loaded packages, global objects, source editor contents, console history). Supports OpenAI', Anthropic (Claude), DeepSeek', Groq', Together AI', OpenRouter', Ollama (fully local, no API key required), and any OpenAI'-compatible custom endpoint (e.g. LM Studio', vLLM', llama.cpp').
Improve your text analysis with languagelayer <https://languagelayer.com>, a powerful language detection API.
Estimate, fit and compare Structural Equation Models (SEM) and network models (Gaussian Graphical Models; GGM) using OpenMx. Allows for two possible generalizations to include GGMs in SEM: GGMs can be used between latent variables (latent network modeling; LNM) or between residuals (residual network modeling; RNM). For details, see Epskamp, Rhemtulla and Borsboom (2017) <doi:10.1007/s11336-017-9557-x>.
Functionalities for calculating the local score and calculating statistical relevance (p-value) to find a local Score in a sequence of given distribution (D. Robelin, S. Déjean, S. Mercier (2025) <doi:10.24072/pcjournal.650> ; S. Mercier and J.-J. Daudin (2001) <https://hal.science/hal-00714174/>) ; S. Karlin and S. Altschul (1990) <https://pmc.ncbi.nlm.nih.gov/articles/PMC53667/> ; S. Mercier, D. Cellier and F. Charlot (2003) <https://hal.science/hal-00937529v1/> ; A. Lagnoux, S. Mercier and P. Valois (2017) <doi:10.1093/bioinformatics/btw699> ).
Latent Markov models for longitudinal continuous and categorical data. See Bartolucci, Pandolfi, Pennoni (2017)<doi:10.18637/jss.v081.i04>.
We present a method based on filtering algorithms to estimate the parameters of linear, i.e. the coefficients and the variance of the error term. The proposed algorithms make use of Particle Filters following Ristic, B., Arulampalam, S., Gordon, N. (2004, ISBN: 158053631X) resampling methods. Parameters of logistic regression models are also estimated using an evolutionary particle filter method.
New empirical Bayes methods aiming at analyzing the association of single nucleotide polymorphisms (SNPs) to some particular disease are implemented in this package. The package uses local false discovery rate (LFDR) estimates of SNPs within a sample population defined as a "reference class" and discovers if SNPs are associated with the corresponding disease. Although SNPs are used throughout this document, other biological data such as protein data and other gene data can be used. Karimnezhad, Ali and Bickel, D. R. (2016) <http://hdl.handle.net/10393/34889>.
Fit right censored Multiple Ordinal Tobit (MOT) model.
This package provides R bindings to the llama.cpp library for running large language models. The package uses a lightweight architecture where the C++ backend library is downloaded at runtime rather than bundled with the package. Package features include text generation, reproducible generation, and parallel inference.
This package provides list-processing utilities inspired by the SRFI-1 list library for Scheme (<https://srfi.schemers.org/srfi-1/srfi-1.html>), including car/cdr family accessors, zip, pairwise, for.each, pair.fold.right and friends. Higher-order helpers that are orthogonal to list processing are deferred to the functional package; this package is freely a mixture of implementation and API.
Computes the probability density function, the cumulative distribution function, the hazard rate function, the quantile function and random generation for Lindley Power Series distributions, see Nadarajah and Si (2018) <doi:10.1007/s13171-018-0150-x>.
User-friendly and generalized tools for the calculation of luck -- moments of variation in metrics like lifespan and lifetime reproductive output. We provide tools for calculating those moments and also performing decompositions into contributions from, for example, individual traits, environmental impacts, and luck (also called individual stochasticity). The functions included here are based on Snyder and Ellner (2024) <doi:10.1086/730557>, Cochran and Ellner (1992) <https://www.jstor.org/stable/2937115>, and Hernandez et al. (2024) <doi:10.1111/ele.14390>.
This package provides a suite of tools to use the eBird database (<https://ebird.org/home/>) and APIs to compare users species lists to recent observations and create a report of the top sites to visit to see new species.
Access to the Greek New Testament (27 books) and the Old Testament (39 books) and allow users to do textual analysis on the data. The New and Old Testament have been provided in their original languages, Greek and Hebrew, respectively. Additionally, the Revised American Standard Bible is also provided for users who'd rather use a wordâ forâ word modern English translation.
Implementation based on Zhang, Jie & Huang, Kun (2014) <doi:10.4137/CIN.S14021> Normalized ImQCM: An Algorithm for Detecting Weak Quasi-Cliques in Weighted Graph with Applications in Gene Co-Expression Module Discovery in Cancers. Cancer informatics, 13, CIN-S14021.
Embarrassingly Parallel Linear Mixed Model calculations spread across local cores which repeat until convergence.