close

Showing 7 of total 7 results (show query)

tidyverse

lubridate:Make Dealing with Dates a Little Easier

Functions to work with date-times and time-spans: fast and user friendly parsing of date-time data, extraction and updating of components of a date-time (years, months, days, hours, minutes, and seconds), algebraic manipulation on date-time and time-span objects. The 'lubridate' package has a consistent and memorable syntax that makes working with dates easy and fun.

Maintained by Vitalie Spinu. Last updated 4 months ago.

datedate-time

757 stars 20.95 score 135k scripts 1.9k dependents

murrayefford

secr:Spatially Explicit Capture-Recapture

Functions to estimate the density and size of a spatially distributed animal population sampled with an array of passive detectors, such as traps, or by searching polygons or transects. Models incorporating distance-dependent detection are fitted by maximizing the likelihood. Tools are included for data manipulation and model selection.

Maintained by Murray Efford. Last updated 5 days ago.

cpp

3 stars 10.06 score 410 scripts 5 dependents

snoweye

phyclust:Phylogenetic Clustering (Phyloclustering)

Phylogenetic clustering (phyloclustering) is an evolutionary Continuous Time Markov Chain model-based approach to identify population structure from molecular data without assuming linkage equilibrium. The package phyclust (Chen 2011) provides a convenient implementation of phyloclustering for DNA and SNP data, capable of clustering individuals into subpopulations and identifying molecular sequences representative of those subpopulations. It is designed in C for performance, interfaced with R for visualization, and incorporates other popular open source programs including ms (Hudson 2002) <doi:10.1093/bioinformatics/18.2.337>, seq-gen (Rambaut and Grassly 1997) <doi:10.1093/bioinformatics/13.3.235>, Hap-Clustering (Tzeng 2005) <doi:10.1002/gepi.20063> and PAML baseml (Yang 1997, 2007) <doi:10.1093/bioinformatics/13.5.555>, <doi:10.1093/molbev/msm088>, for simulating data, additional analyses, and searching the best tree. See the phyclust website for more information, documentations and examples.

Maintained by Wei-Chen Chen. Last updated 2 years ago.

9 stars 8.45 score 126 scripts 8 dependents

chgrl

bReeze:Functions for Wind Resource Assessment

A collection of functions to analyse, visualize and interpret wind data and to calculate the potential energy production of wind turbines.

Maintained by Christian Graul. Last updated 1 years ago.

20 stars 4.34 score 22 scripts

lmaowisc

rmt:Restricted Mean Time in Favor of Treatment

Contains inferential and graphical routines for comparing two treatment arms in terms of the restricted mean time in favor of treatment.

Maintained by Lu Mao. Last updated 3 months ago.

4.34 score 22 scripts

fergusreiggracia

ClimInd:Climate Indices

Computes 138 standard climate indices at monthly, seasonal and annual resolution. These indices were selected, based on their direct and significant impacts on target sectors, after a thorough review of the literature in the field of extreme weather events and natural hazards. Overall, the selected indices characterize different aspects of the frequency, intensity and duration of extreme events, and are derived from a broad set of climatic variables, including surface air temperature, precipitation, relative humidity, wind speed, cloudiness, solar radiation, and snow cover. The 138 indices have been classified as follow: Temperature based indices (42), Precipitation based indices (22), Bioclimatic indices (21), Wind-based indices (5), Aridity/ continentality indices (10), Snow-based indices (13), Cloud/radiation based indices (6), Drought indices (8), Fire indices (5), Tourism indices (5).

Maintained by Fergus Reig-Gracia. Last updated 13 days ago.

3.74 score 22 scripts

jeinbeck-code

LPCM:Local Principal Curve Methods

Fitting multivariate data patterns with local principal curves, including tools for data compression (projection) and measuring goodness-of-fit; with some additional functions for mean shift clustering. See Einbeck, Tutz and Evers (2005) <doi:10.1007/s11222-005-4073-8> and Ameijeiras-Alonso and Einbeck (2023) <doi:10.1007/s11634-023-00575-1>.

Maintained by Jochen Einbeck. Last updated 7 months ago.

3.09 score 35 scripts 1 dependents

: