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taxodist - Taxonomic Hierarchy Distances and Lineage Analysis

Computes distances between taxonomic hierarchy nodes using lineage data retrieved from The Taxonomicon <http://taxonomicon.taxonomy.nl>. For distinct nodes, distance is defined as the reciprocal of the depth of their most recent common ancestor; identical nodes have distance zero. This definition yields an ultrametric within each connected hierarchy. Functions are provided for auditable name resolution, online or user-supplied lineage analysis, clade membership, pairwise, matrix, and cross-set distance calculation, classification trees with named clades, hierarchical clustering, principal coordinates analysis, portable and comparable JSON analysis bundles, and cache management. Distance matrices are returned as base R 'dist' objects. The distances represent classification depth rather than evolutionary time or phylogenetic branch length.

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5.77 score 2 stars 15 scripts 404 downloads

Rtwalk - An MCMC Sampler Using the t-Walk Algorithm

Implements the t-walk algorithm, a general-purpose, self-adjusting Markov Chain Monte Carlo (MCMC) sampler for continuous distributions as described by Christen & Fox (2010) <doi:10.1214/10-BA603>. The t-walk requires no tuning and is robust for a wide range of target distributions, including high-dimensional and multimodal problems. This implementation includes an option for running multiple chains in parallel to accelerate sampling and facilitate convergence diagnostics.

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4.94 score 35 scripts 333 downloads

margEVT - Regularized Point Processes and Stochastic Marginalization for Extremes

Implements a non-stationary extreme value analysis framework by coupling a covariate-driven non-homogeneous Poisson process (NHPP) with (adaptive) elastic-net regularization and analytical gradients. Provides methods for estimating conditional return levels and unconditional (marginalized) return levels via parametric stochastic integration over stable vector autoregressive VAR(p) covariate trajectories, or non-parametric annual-block resampling. Supports block-specific penalty controls, BIC selection along a regularization path, Karush-Kuhn-Tucker convergence checks, time-rescaling residual diagnostics, conditional parametric bootstrap inference, and walk-forward assessment.

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4.54 score 7 scripts 273 downloads

rmet - Download and Read Brazilian Meteorological Data from INMET

Automates the download and processing of historical weather data from the Brazilian National Institute of Meteorology (INMET). It provides a cached catalogue of automatic stations, resumable and validated downloads, and parsers for formatting inconsistencies in raw CSV files across different years. It removes structural artifacts, standardizes column names, parses timestamps, and returns data frames ready for analysis. Data are retrieved from <https://portal.inmet.gov.br/dadoshistoricos> and <https://apitempo.inmet.gov.br/estacoes/T>.

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4.18 score 3 scripts 328 downloads

EDE - Extinction Date Estimation from Sighting Records

Estimates the historic date of extinction of a species from a time-ordered record of sighting events. Given a table of sighting counts per year, computes extinction date estimators from the sighting-record literature: optimal linear estimation and its Weibull extreme-value persistence test (Roberts & Solow, 2003; Solow, 2005), constant-rate and declining-rate persistence tests (Solow, 1993), a sighting-rate persistence test comparable across records with different observation periods (McInerny, Roberts, Davy & Cribb, 2006), a classical confidence interval on the end of a temporal range (Strauss & Sadler, 1989), a truncation-point extrapolation (Robson & Whitlock, 1964), and a combinatorial persistence test based on inclusion-exclusion over sighting-gap occupancy (Burgman, Grimson & Ferson, 1995). Also implements a nonparametric endpoint test (Solow & Roberts, 2003), a sighting-interval trend index (Jarić & Ebenhard, 2010), and reliability-adjusted inference for uncertain records (Jarić & Roberts, 2014). Every estimator is built on a validated input object and returns a common result class with, where defined, a point estimate, a confidence interval, or a full p-value curve.

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4.00 score 3 scripts 170 downloads