Showing 8 of total 8 results (show query)
hwborchers
pracma:Practical Numerical Math Functions
Provides a large number of functions from numerical analysis and linear algebra, numerical optimization, differential equations, time series, plus some well-known special mathematical functions. Uses 'MATLAB' function names where appropriate to simplify porting.
Maintained by Hans W. Borchers. Last updated 1 years ago.
29 stars 12.34 score 6.6k scripts 931 dependents
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
byoungman
evgam:Generalised Additive Extreme Value Models
Methods for fitting various extreme value distributions with parameters of generalised additive model (GAM) form are provided. For details of distributions see Coles, S.G. (2001) <doi:10.1007/978-1-4471-3675-0>, GAMs see Wood, S.N. (2017) <doi:10.1201/9781315370279>, and the fitting approach see Wood, S.N., Pya, N. & Safken, B. (2016) <doi:10.1080/01621459.2016.1180986>. Details of how evgam works and various examples are given in Youngman, B.D. (2022) <doi:10.18637/jss.v103.i03>.
Maintained by Ben Youngman. Last updated 20 days ago.
6 stars 8.43 score 82 scripts 12 dependents
cwatson
brainGraph:Graph Theory Analysis of Brain MRI Data
A set of tools for performing graph theory analysis of brain MRI data. It works with data from a Freesurfer analysis (cortical thickness, volumes, local gyrification index, surface area), diffusion tensor tractography data (e.g., from FSL) and resting-state fMRI data (e.g., from DPABI). It contains a graphical user interface for graph visualization and data exploration, along with several functions for generating useful figures.
Maintained by Christopher G. Watson. Last updated 1 years ago.
brain-connectivitybrain-imagingcomplex-networksconnectomeconnectomicsfmrigraph-theorymrinetwork-analysisneuroimagingneurosciencestatisticstractography
188 stars 7.86 score 107 scripts 3 dependents
svkucheryavski
mdatools:Multivariate Data Analysis for Chemometrics
Projection based methods for preprocessing, exploring and analysis of multivariate data used in chemometrics. S. Kucheryavskiy (2020) <doi:10.1016/j.chemolab.2020.103937>.
Maintained by Sergey Kucheryavskiy. Last updated 8 months ago.
36 stars 7.41 score 220 scripts 1 dependents
r-cas
caracas:Computer Algebra
Computer algebra via the 'SymPy' library (<https://www.sympy.org/>). This makes it possible to solve equations symbolically, find symbolic integrals, symbolic sums and other important quantities.
Maintained by Mikkel Meyer Andersen. Last updated 1 months ago.
24 stars 6.80 score 87 scripts 1 dependents
data-cleaning
lintools:Manipulation of Linear Systems of (in)Equalities
Variable elimination (Gaussian elimination, Fourier-Motzkin elimination), Moore-Penrose pseudoinverse, reduction to reduced row echelon form, value substitution, projecting a vector on the convex polytope described by a system of (in)equations, simplify systems by removing spurious columns and rows and collapse implied equalities, test if a matrix is totally unimodular, compute variable ranges implied by linear (in)equalities.
Maintained by Mark van der Loo. Last updated 10 months ago.
4 stars 5.19 score 13 scripts 2 dependents
chemhouse-group
rchemo:Dimension Reduction, Regression and Discrimination for Chemometrics
Data exploration and prediction with focus on high dimensional data and chemometrics. The package was initially designed about partial least squares regression and discrimination models and variants, in particular locally weighted PLS models (LWPLS). Then, it has been expanded to many other methods for analyzing high dimensional data. The name 'rchemo' comes from the fact that the package is orientated to chemometrics, but most of the provided methods are fully generic to other domains. Functions such as transform(), predict(), coef() and summary() are available. Tuning the predictive models is facilitated by generic functions gridscore() (validation dataset) and gridcv() (cross-validation). Faster versions are also available for models based on latent variables (LVs) (gridscorelv() and gridcvlv()) and ridge regularization (gridscorelb() and gridcvlb()).
Maintained by Marion Brandolini-Bunlon. Last updated 7 months ago.
3 stars 3.52 score 11 scripts