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DoE.base is a foundational R package by Ulrike Groemping for full factorial experimental designs and designs based on orthogonal arrays. It provides utility functions for the shared `design` class use
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Install the MCP server or CLI to instantly fetch Doebase documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/doebase
mvabund is an R package providing a model-based approach to analyzing multivariate abundance data in ecology. It offers tools for data visualization, fitting predictive generalized linear models (GLMs
2 shared topics • 3 shared operations
Hmsc (Hierarchical Modelling of Species Communities) is an R package for fitting joint species distribution models (JSDMs) in a Bayesian hierarchical framework. It links species occurrences or abundan
1 shared topic • 2 shared operations
WeatherBench 2 is a benchmarking framework for next-generation data-driven global weather models. It provides tools for accessing re-forecast and observational data, computing performance metrics (RMS
1 shared topic • 2 shared operations
OceanParcels (Parcels) is a Python framework for Lagrangian ocean analysis: it tracks virtual particles through 2D/3D hydrodynamic velocity fields from ocean models or observational products. Use this
2 shared topics
fdrtool — estimation of tail area-based false discovery rates (Fdr/q-values) and density-based local false discovery rates (fdr) from observed test statistics. Supports four null models: normal (z-sco
1 shared topic • 1 shared operation