Use when working with Convex.jl — a Julia package for Disciplined Convex Programming (DCP) that formulates and solves convex optimization problems with natural mathematical syntax. Covers problem cons
Use with AI
Install the MCP server or CLI to instantly fetch Convexjl documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/convexjl
Use when working with CVXPY — a Python-embedded domain-specific language for convex optimization problems. Covers problem construction with the DCP (Disciplined Convex Programming) ruleset, all built-
1 shared topic • 2 shared operations
NCO (netCDF Operators) is a suite of command-line programs that manipulate and analyze data stored in netCDF-accessible formats, including DAP, HDF4, HDF5, and Zarr. Primary use cases include metadata
2 shared topics
Bambi (BAyesian Model-Building Interface) is a high-level Python package for fitting Bayesian generalized linear and generalized linear mixed models using a concise, R-style Wilkinson formula syntax.
1 shared topic • 1 shared operation
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
1 shared topic • 1 shared operation
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
1 shared topic • 1 shared operation