Scientific Software
Updated 6 months ago

univariateML — Peer-reviewed • Rank 10.6 • Science 95%

univariateML: An R package for maximum likelihood estimation of univariate densities - Published in JOSS (2019)

Earth and Environmental Sciences (40%)
Scientific Software · Peer-reviewed
Scientific Software
Updated 6 months ago

EDP — Peer-reviewed • Rank 4.8 • Science 98%

EDP: a program for projecting electron densities from VASP onto planes - Published in JOSS (2023)

Scientific Software · Peer-reviewed
Updated 6 months ago

velocityconversion • Rank 5.4 • Science 67%

Python implementation of mantle velocity conversion by Goes et al. (2000).

Updated 6 months ago

gnss_rr • Rank 1.6 • Science 57%

Continuous estimation of snow/firn accumulation, surface mass, and density on a moving surface using combined GNSS reflectometry/refractometry (GNSS-RR)}

Updated 6 months ago

gnss_rr • Rank 1.4 • Science 57%

Continuous estimation of snow/firn accumulation, surface mass, and density on a moving surface using combined GNSS reflectometry/refractometry (GNSS-RR)

Updated 6 months ago

@stdlib/stats-base-dists-kumaraswamy-logpdf • Rank 4.6 • Science 44%

Natural logarithm of the probability density function (PDF) for a Kumaraswamy's double bounded distribution.

Updated 6 months ago

stats-base-dists-negative-binomial-logpmf • Rank 0.7 • Science 44%

Natural logarithm of the probability mass function (PMF) for a negative binomial distribution.

Updated 5 months ago

https://github.com/spsanderson/tidydensity • Rank 4.7 • Science 36%

Create tidy probability/density tibbles and plots of randomly generated and empirical data.

Updated 6 months ago

kernelboot • Rank 12.9 • Science 13%

Smoothed bootstrap and functions for sampling from kernel densities

Updated 6 months ago

densegastoolbox • Science 44%

Calculate density and temperature from observed molecular lines (CO, HCN, HNC, HCO+ etc)

Updated 6 months ago

rrlab • Science 44%

The RRLab R package is a growing collection of experimental techniques and quality-of-life tools born from years of hands-on data science, modeling, and exploration. Built as a personal lab bench in R, it reflects a constant search for better ways to understand high-dimensional data, test bold ideas, and streamline the grind of daily analysis.