Showing 5 of total 5 results (show query)
covaruber
sommer:Solving Mixed Model Equations in R
Structural multivariate-univariate linear mixed model solver for estimation of multiple random effects with unknown variance-covariance structures (e.g., heterogeneous and unstructured) and known covariance among levels of random effects (e.g., pedigree and genomic relationship matrices) (Covarrubias-Pazaran, 2016 <doi:10.1371/journal.pone.0156744>; Maier et al., 2015 <doi:10.1016/j.ajhg.2014.12.006>; Jensen et al., 1997). REML estimates can be obtained using the Direct-Inversion Newton-Raphson and Direct-Inversion Average Information algorithms for the problems r x r (r being the number of records) or using the Henderson-based average information algorithm for the problem c x c (c being the number of coefficients to estimate). Spatial models can also be fitted using the two-dimensional spline functionality available.
Maintained by Giovanny Covarrubias-Pazaran. Last updated 4 days ago.
average-informationmixed-modelsrcpparmadilloopenblascppopenmp
44 stars 12.63 score 300 scripts 10 dependents
luca-scr
GA:Genetic Algorithms
Flexible general-purpose toolbox implementing genetic algorithms (GAs) for stochastic optimisation. Binary, real-valued, and permutation representations are available to optimize a fitness function, i.e. a function provided by users depending on their objective function. Several genetic operators are available and can be combined to explore the best settings for the current task. Furthermore, users can define new genetic operators and easily evaluate their performances. Local search using general-purpose optimisation algorithms can be applied stochastically to exploit interesting regions. GAs can be run sequentially or in parallel, using an explicit master-slave parallelisation or a coarse-grain islands approach. For more details see Scrucca (2013) <doi:10.18637/jss.v053.i04> and Scrucca (2017) <doi:10.32614/RJ-2017-008>.
Maintained by Luca Scrucca. Last updated 7 months ago.
genetic-algorithmoptimisationcpp
93 stars 11.58 score 624 scripts 52 dependents
bioc
Cardinal:A mass spectrometry imaging toolbox for statistical analysis
Implements statistical & computational tools for analyzing mass spectrometry imaging datasets, including methods for efficient pre-processing, spatial segmentation, and classification.
Maintained by Kylie Ariel Bemis. Last updated 3 months ago.
softwareinfrastructureproteomicslipidomicsmassspectrometryimagingmassspectrometryimmunooncologynormalizationclusteringclassificationregression
48 stars 10.32 score 200 scripts
rubenfcasal
npsp:Nonparametric Spatial Statistics
Multidimensional nonparametric spatial (spatio-temporal) geostatistics. S3 classes and methods for multidimensional: linear binning, local polynomial kernel regression (spatial trend estimation), density and variogram estimation. Nonparametric methods for simultaneous inference on both spatial trend and variogram functions (for spatial processes). Nonparametric residual kriging (spatial prediction). For details on these methods see, for example, Fernandez-Casal and Francisco-Fernandez (2014) <doi:10.1007/s00477-013-0817-8> or Castillo-Paez et al. (2019) <doi:10.1016/j.csda.2019.01.017>.
Maintained by Ruben Fernandez-Casal. Last updated 5 months ago.
geostatisticsspatial-data-analysisstatisticsfortranopenblas
4 stars 5.71 score 64 scripts
cran
matlab:'MATLAB' Emulation Package
Emulate 'MATLAB' code using 'R'.
Maintained by P. Roebuck. Last updated 9 months ago.
4.09 score 19 dependents