Showing 12 of total 12 results (show query)
therneau
survival:Survival Analysis
Contains the core survival analysis routines, including definition of Surv objects, Kaplan-Meier and Aalen-Johansen (multi-state) curves, Cox models, and parametric accelerated failure time models.
Maintained by Terry M Therneau. Last updated 3 months ago.
400 stars 20.40 score 29k scripts 3.9k dependents
kkholst
mets:Analysis of Multivariate Event Times
Implementation of various statistical models for multivariate event history data <doi:10.1007/s10985-013-9244-x>. Including multivariate cumulative incidence models <doi:10.1002/sim.6016>, and bivariate random effects probit models (Liability models) <doi:10.1016/j.csda.2015.01.014>. Modern methods for survival analysis, including regression modelling (Cox, Fine-Gray, Ghosh-Lin, Binomial regression) with fast computation of influence functions.
Maintained by Klaus K. Holst. Last updated 22 hours ago.
multivariate-time-to-eventsurvival-analysistime-to-eventfortranopenblascpp
14 stars 13.45 score 236 scripts 42 dependents
thibautjombart
adegenet:Exploratory Analysis of Genetic and Genomic Data
Toolset for the exploration of genetic and genomic data. Adegenet provides formal (S4) classes for storing and handling various genetic data, including genetic markers with varying ploidy and hierarchical population structure ('genind' class), alleles counts by populations ('genpop'), and genome-wide SNP data ('genlight'). It also implements original multivariate methods (DAPC, sPCA), graphics, statistical tests, simulation tools, distance and similarity measures, and several spatial methods. A range of both empirical and simulated datasets is also provided to illustrate various methods.
Maintained by Zhian N. Kamvar. Last updated 2 months ago.
182 stars 12.60 score 1.9k scripts 29 dependents
markmfredrickson
optmatch:Functions for Optimal Matching
Distance based bipartite matching using minimum cost flow, oriented to matching of treatment and control groups in observational studies ('Hansen' and 'Klopfer' 2006 <doi:10.1198/106186006X137047>). Routines are provided to generate distances from generalised linear models (propensity score matching), formulas giving variables on which to limit matched distances, stratified or exact matching directives, or calipers, alone or in combination.
Maintained by Josh Errickson. Last updated 4 months ago.
47 stars 12.22 score 588 scripts 5 dependents
jmsigner
amt:Animal Movement Tools
Manage and analyze animal movement data. The functionality of 'amt' includes methods to calculate home ranges, track statistics (e.g. step lengths, speed, or turning angles), prepare data for fitting habitat selection analyses, and simulation of space-use from fitted step-selection functions.
Maintained by Johannes Signer. Last updated 5 months ago.
41 stars 10.54 score 418 scripts
goranbrostrom
eha:Event History Analysis
Parametric proportional hazards fitting with left truncation and right censoring for common families of distributions, piecewise constant hazards, and discrete models. Parametric accelerated failure time models for left truncated and right censored data. Proportional hazards models for tabular and register data. Sampling of risk sets in Cox regression, selections in the Lexis diagram, bootstrapping. Broström (2022) <doi:10.1201/9780429503764>.
Maintained by Göran Broström. Last updated 10 months ago.
7 stars 9.76 score 308 scripts 10 dependents
alinamateikondylis
sampling:Survey Sampling
Functions to draw random samples using different sampling schemes are available. Functions are also provided to obtain (generalized) calibration weights, different estimators, as well some variance estimators.
Maintained by Alina Matei. Last updated 1 years ago.
2 stars 8.08 score 772 scripts 29 dependents
murrayefford
openCR:Open Population Capture-Recapture
Non-spatial and spatial open-population capture-recapture analysis.
Maintained by Murray Efford. Last updated 5 months ago.
4 stars 5.98 score 53 scripts
bafuentes
rassta:Raster-Based Spatial Stratification Algorithms
Algorithms for the spatial stratification of landscapes, sampling and modeling of spatially-varying phenomena. These algorithms offer a simple framework for the stratification of geographic space based on raster layers representing landscape factors and/or factor scales. The stratification process follows a hierarchical approach, which is based on first level units (i.e., classification units) and second-level units (i.e., stratification units). Nonparametric techniques allow to measure the correspondence between the geographic space and the landscape configuration represented by the units. These correspondence metrics are useful to define sampling schemes and to model the spatial variability of environmental phenomena. The theoretical background of the algorithms and code examples are presented in Fuentes, Dorantes, and Tipton (2021). <doi:10.31223/X50S57>.
Maintained by Bryan A. Fuentes. Last updated 3 years ago.
ecologygeoinformaticshierarchicalmodelingsamplingspatial
16 stars 5.96 score 19 scripts
ucd-serg
serocalculator:Estimating Infection Rates from Serological Data
Translates antibody levels measured in cross-sectional population samples into estimates of the frequency with which seroconversions (infections) occur in the sampled populations. Replaces the previous `seroincidence` package.
Maintained by Kristina Lai. Last updated 5 days ago.
epidemiologyincidence-estimationseroepidemiology
6 stars 5.61 score 13 scripts
psolymos
opticut:Likelihood Based Optimal Partitioning and Indicator Species Analysis
Likelihood based optimal partitioning and indicator species analysis. Finding the best binary partition for each species based on model selection, with the possibility to take into account modifying/confounding variables as described in Kemencei et al. (2014) <doi:10.1556/ComEc.15.2014.2.6>. The package implements binary and multi-level response models, various measures of uncertainty, Lorenz-curve based thresholding, with native support for parallel computations.
Maintained by Peter Solymos. Last updated 10 months ago.
ecologyindicator-species-analysislikelihoodoptimal-partitioningspecies
2 stars 3.91 score 82 scripts
cran
SDAR:Stratigraphic Data Analysis
A fast, consistent tool for plotting and facilitating the analysis of stratigraphic and sedimentological data. Taking advantage of the flexible plotting tools available in R, 'SDAR' uses stratigraphic and sedimentological data to produce detailed graphic logs for outcrop sections and borehole logs. These logs can include multiple features (e.g., bed thickness, lithology, samples, sedimentary structures, colors, fossil content, bioturbation index, gamma ray logs) (Johnson, 1992, <ISSN 0037-0738>).
Maintained by John R. Ortiz. Last updated 4 years ago.
3.30 score