close

Showing 18 of total 18 results (show query)

renkun-ken

formattable:Create 'Formattable' Data Structures

Provides functions to create formattable vectors and data frames. 'Formattable' vectors are printed with text formatting, and formattable data frames are printed with multiple types of formatting in HTML to improve the readability of data presented in tabular form rendered in web pages.

Maintained by Kun Ren. Last updated 4 months ago.

700 stars 14.69 score 3.6k scripts 26 dependents

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

karlines

rootSolve:Nonlinear Root Finding, Equilibrium and Steady-State Analysis of Ordinary Differential Equations

Routines to find the root of nonlinear functions, and to perform steady-state and equilibrium analysis of ordinary differential equations (ODE). Includes routines that: (1) generate gradient and jacobian matrices (full and banded), (2) find roots of non-linear equations by the 'Newton-Raphson' method, (3) estimate steady-state conditions of a system of (differential) equations in full, banded or sparse form, using the 'Newton-Raphson' method, or by dynamically running, (4) solve the steady-state conditions for uni-and multicomponent 1-D, 2-D, and 3-D partial differential equations, that have been converted to ordinary differential equations by numerical differencing (using the method-of-lines approach). Includes fortran code.

Maintained by Karline Soetaert. Last updated 2 years ago.

fortran

1 stars 9.61 score 1.2k scripts 216 dependents

jonclayden

shades:Simple Colour Manipulation

Functions for easily manipulating colours, creating colour scales and calculating colour distances.

Maintained by Jon Clayden. Last updated 6 months ago.

colorcolor-manipulationcolourcolour-manipulationcolour-spaces

83 stars 9.58 score 178 scripts 37 dependents

otoomet

maxLik:Maximum Likelihood Estimation and Related Tools

Functions for Maximum Likelihood (ML) estimation, non-linear optimization, and related tools. It includes a unified way to call different optimizers, and classes and methods to handle the results from the Maximum Likelihood viewpoint. It also includes a number of convenience tools for testing and developing your own models.

Maintained by Ott Toomet. Last updated 1 years ago.

9.14 score 480 scripts 110 dependents

eguidotti

calculus:High Dimensional Numerical and Symbolic Calculus

Efficient C++ optimized functions for numerical and symbolic calculus as described in Guidotti (2022) <doi:10.18637/jss.v104.i05>. It includes basic arithmetic, tensor calculus, Einstein summing convention, fast computation of the Levi-Civita symbol and generalized Kronecker delta, Taylor series expansion, multivariate Hermite polynomials, high-order derivatives, ordinary differential equations, differential operators (Gradient, Jacobian, Hessian, Divergence, Curl, Laplacian) and numerical integration in arbitrary orthogonal coordinate systems: cartesian, polar, spherical, cylindrical, parabolic or user defined by custom scale factors.

Maintained by Emanuele Guidotti. Last updated 2 years ago.

calculuscoordinate-systemscurldivergenceeinsteinfinite-differencegradienthermitehessianjacobianlaplaciannumerical-derivationnumerical-derivativesnumerical-differentiationsymbolic-computationsymbolic-differentiationtaylorcpp

47 stars 8.98 score 66 scripts 7 dependents

robinhankin

hyper2:The Hyperdirichlet Distribution, Mark 2

A suite of routines for the hyperdirichlet distribution and reified Bradley-Terry; supersedes the 'hyperdirichlet' package; uses 'disordR' discipline <doi:10.48550/ARXIV.2210.03856>. To cite in publications please use Hankin 2017 <doi:10.32614/rj-2017-061>, and for Generalized Plackett-Luce likelihoods use Hankin 2024 <doi:10.18637/jss.v109.i08>.

Maintained by Robin K. S. Hankin. Last updated 15 hours ago.

cpp

5 stars 7.91 score 38 scripts 1 dependents

jdtuck

fdasrvf:Elastic Functional Data Analysis

Performs alignment, PCA, and modeling of multidimensional and unidimensional functions using the square-root velocity framework (Srivastava et al., 2011 <doi:10.48550/arXiv.1103.3817> and Tucker et al., 2014 <DOI:10.1016/j.csda.2012.12.001>). This framework allows for elastic analysis of functional data through phase and amplitude separation.

Maintained by J. Derek Tucker. Last updated 1 months ago.

openblascppopenmp

13 stars 7.79 score 83 scripts 3 dependents

dkahle

mpoly:Symbolic Computation and More with Multivariate Polynomials

Symbolic computing with multivariate polynomials in R.

Maintained by David Kahle. Last updated 4 months ago.

12 stars 6.25 score 70 scripts 7 dependents

roliveros-ramos

calibrar:Automated Parameter Estimation for Complex Models

General optimisation and specific tools for the parameter estimation (i.e. calibration) of complex models, including stochastic ones. It implements generic functions that can be used for fitting any type of models, especially those with non-differentiable objective functions, with the same syntax as 'stats::optim()'. It supports multiple phases estimation (sequential parameter masking), constrained optimization (bounding box restrictions) and automatic parallel computation of numerical gradients. Some common maximum likelihood estimation methods and automated construction of the objective function from simulated model outputs is provided. See <https://roliveros-ramos.github.io/calibrar/> for more details.

Maintained by Ricardo Oliveros-Ramos. Last updated 3 days ago.

modelingoptimizationoptimization-methods

7 stars 6.18 score 27 scripts

konrad1991

dfdr:Automatic Differentiation of Simple Functions

Implementation of automatically computing derivatives of functions (see Mailund Thomas (2017) <doi:10.1007/978-1-4842-2881-4>). Moreover, calculating gradients, Hessian and Jacobian matrices is possible.

Maintained by Konrad Krämer. Last updated 1 months ago.

7 stars 5.27 score 11 scripts 2 dependents

pi-kappa-devel

markets:Estimation Methods for Markets in Equilibrium and Disequilibrium

Provides estimation methods for markets in equilibrium and disequilibrium. Supports the estimation of an equilibrium and four disequilibrium models with both correlated and independent shocks. Also provides post-estimation analysis tools, such as aggregation, marginal effect, and shortage calculations. See Karapanagiotis (2024) <doi:10.18637/jss.v108.i02> for an overview of the functionality and examples. The estimation methods are based on full information maximum likelihood techniques given in Maddala and Nelson (1974) <doi:10.2307/1914215>. They are implemented using the analytic derivative expressions calculated in Karapanagiotis (2020) <doi:10.2139/ssrn.3525622>. Standard errors can be estimated by adjusting for heteroscedasticity or clustering. The equilibrium estimation constitutes a case of a system of linear, simultaneous equations. Instead, the disequilibrium models replace the market-clearing condition with a non-linear, short-side rule and allow for different specifications of price dynamics.

Maintained by Pantelis Karapanagiotis. Last updated 1 years ago.

disequilibriumeconomicsfinancefull-information-maximum-likelihoodmarket-clearingmarket-modelsshort-side-rulecpp

1 stars 4.30 score 9 scripts

cran

bst:Gradient Boosting

Functional gradient descent algorithm for a variety of convex and non-convex loss functions, for both classical and robust regression and classification problems. See Wang (2011) <doi:10.2202/1557-4679.1304>, Wang (2012) <doi:10.3414/ME11-02-0020>, Wang (2018) <doi:10.1080/10618600.2018.1424635>, Wang (2018) <doi:10.1214/18-EJS1404>.

Maintained by Zhu Wang. Last updated 2 years ago.

4.17 score 5 dependents

techtonique

bcn:Boosted Configuration Networks

Boosted Configuration (neural) Networks for supervised learning.

Maintained by T. Moudiki. Last updated 6 months ago.

machine-learningneural-networksstatistical-learningcpp

5 stars 4.00 score 4 scripts

obreschkow

cooltools:Practical Tools for Scientific Computations and Visualizations

Collection of routines for efficient scientific computations in physics and astrophysics. These routines include utility functions, numerical computation tools, as well as visualisation tools. They can be used, for example, for generating random numbers from spherical and custom distributions, information and entropy analysis, special Fourier transforms, two-point correlation estimation (e.g. as in Landy & Szalay (1993) <doi:10.1086/172900>), binning & gridding of point sets, 2D interpolation, Monte Carlo integration, vector arithmetic and coordinate transformations. Also included is a non-exhaustive list of important constants and cosmological conversion functions. The graphics routines can be used to produce and export publication-ready scientific plots and movies, e.g. as used in Obreschkow et al. (2020, MNRAS Vol 493, Issue 3, Pages 4551–4569). These routines include special color scales, projection functions, and bitmap handling routines.

Maintained by Danail Obreschkow. Last updated 4 months ago.

cpp

1 stars 3.17 score 21 scripts

cran

weakARMA:Tools for the Analysis of Weak ARMA Models

Numerous time series admit autoregressive moving average (ARMA) representations, in which the errors are uncorrelated but not necessarily independent. These models are called weak ARMA by opposition to the standard ARMA models, also called strong ARMA models, in which the error terms are supposed to be independent and identically distributed (iid). This package allows the study of nonlinear time series models through weak ARMA representations. It determines identification, estimation and validation for ARMA models and for AR and MA models in particular. Functions can also be used in the strong case. This package also works on white noises by omitting arguments 'p', 'q', 'ar' and 'ma'. See Francq, C. and Zakoïan, J. (1998) <doi:10.1016/S0378-3758(97)00139-0> and Boubacar Maïnassara, Y. and Saussereau, B. (2018) <doi:10.1080/01621459.2017.1380030> for more details.

Maintained by Julien Yves Rolland. Last updated 3 years ago.

1.70 score

yblan

optimalThreshold:Bayesian Methods for Optimal Threshold Estimation

Functions to estimate the optimal threshold of diagnostic markers or treatment selection markers. The optimal threshold is the marker value that maximizes the utility of the marker based-strategy (for diagnostic or treatment selection) in a given population. The utility function depends on the type of marker (diagnostic or treatment selection), but always takes into account the preferences of the patients or the physician in the decision process. For estimating the optimal threshold, ones must specify the distributions of the marker in different groups (defined according to the type of marker, diagnostic or treatment selection) and provides data to estimate the parameters of these distributions. Ones must also provide some features of the target populations (disease prevalence or treatment efficacies) as well as the preferences of patients or physicians. The functions rely on Bayesian inference which helps producing several indicators derived from the optimal threshold. See Blangero, Y, Rabilloud, M, Ecochard, R, and Subtil, F (2019) <doi:10.1177/0962280218821394> for the original article that describes the estimation method for treatment selection markers and Subtil, F, and Rabilloud, M (2019) <doi:10.1002/bimj.200900242> for diagnostic markers.

Maintained by Yoann Blangero. Last updated 5 years ago.

jagscpp

1.00 score

linusseelinger

umbridge:Integration for the UM-Bridge Protocol

A convenient wrapper for the UM-Bridge protocol. UM-Bridge is a protocol designed for coupling uncertainty quantification (or statistical / optimization) software to numerical models. A model is represented as a mathematical function with optional support for derivatives via Jacobian actions etc.

Maintained by Linus Seelinger. Last updated 3 years ago.

1.00 score 5 scripts

: