Showing 4 of total 4 results (show query)
bioc
matter:Out-of-core statistical computing and signal processing
Toolbox for larger-than-memory scientific computing and visualization, providing efficient out-of-core data structures using files or shared memory, for dense and sparse vectors, matrices, and arrays, with applications to nonuniformly sampled signals and images.
Maintained by Kylie A. Bemis. Last updated 4 months ago.
infrastructuredatarepresentationdataimportdimensionreductionpreprocessingcpp
57 stars 9.52 score 64 scripts 2 dependents
asa12138
pcutils:Some Useful Functions for Statistics and Visualization
Offers a range of utilities and functions for everyday programming tasks. 1.Data Manipulation. Such as grouping and merging, column splitting, and character expansion. 2.File Handling. Read and convert files in popular formats. 3.Plotting Assistance. Helpful utilities for generating color palettes, validating color formats, and adding transparency. 4.Statistical Analysis. Includes functions for pairwise comparisons and multiple testing corrections, enabling perform statistical analyses with ease. 5.Graph Plotting, Provides efficient tools for creating doughnut plot and multi-layered doughnut plot; Venn diagrams, including traditional Venn diagrams, upset plots, and flower plots; Simplified functions for creating stacked bar plots, or a box plot with alphabets group for multiple comparison group.
Maintained by Chen Peng. Last updated 6 days ago.
22 stars 6.47 score 28 scripts 4 dependents
benjaminhlina
trps:Bayesian Trophic Position Models using 'stan'
Bayesian trophic position models using 'stan' by leveraging 'brms' for stable isotope data. Trophic position models are derived by using equations from Post (2002) <doi:10.1890/0012-9658(2002)083[0703:USITET]2.0.CO;2>, Vander Zanden and Vadeboncoeur (2002) <doi:10.1890/0012-9658(2002)083[2152:FAIOBA]2.0.CO;2>, and Heuvel et al. (2024) <doi:10.1139/cjfas-2024-0028>.
Maintained by Benjamin L. Hlina. Last updated 11 days ago.
3.54 score 4 scripts
cran
trps:Bayesian Trophic Position Models using 'stan'
Bayesian trophic position models using 'stan' by leveraging 'brms' for stable isotope data. Trophic position models are derived by using equations from Post (2002) <doi:10.1890/0012-9658(2002)083[0703:USITET]2.0.CO;2>, Vander Zanden and Vadeboncoeur (2002) <doi:10.1890/0012-9658(2002)083[2152:FAIOBA]2.0.CO;2>, and Heuvel et al. (2024) <doi:10.1139/cjfas-2024-0028>.
Maintained by Benjamin L. Hlina. Last updated 12 days ago.
2.70 score