R-universe search: exports:ridge

Showing 9 of total 9 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

jhorzek

lessSEM:Non-Smooth Regularization for Structural Equation Models

Provides regularized structural equation modeling (regularized SEM) with non-smooth penalty functions (e.g., lasso) building on 'lavaan'. The package is heavily inspired by the ['regsem'](<https://github.com/Rjacobucci/regsem>) and ['lslx'](<https://github.com/psyphh/lslx>) packages.

Maintained by Jannik H. Orzek. Last updated 1 years ago.

lasso psychometrics regularization regularized-structural-equation-model sem structural-equation-modeling openblas cpp openmp

7 stars 7.19 score 223 scripts

faosorios

fastmatrix:Fast Computation of some Matrices Useful in Statistics

Small set of functions to fast computation of some matrices and operations useful in statistics and econometrics. Currently, there are functions for efficient computation of duplication, commutation and symmetrizer matrices with minimal storage requirements. Some commonly used matrix decompositions (LU and LDL), basic matrix operations (for instance, Hadamard, Kronecker products and the Sherman-Morrison formula) and iterative solvers for linear systems are also available. In addition, the package includes a number of common statistical procedures such as the sweep operator, weighted mean and covariance matrix using an online algorithm, linear regression (using Cholesky, QR, SVD, sweep operator and conjugate gradients methods), ridge regression (with optimal selection of the ridge parameter considering several procedures), omnibus tests for univariate normality, functions to compute the multivariate skewness, kurtosis, the Mahalanobis distance (checking the positive defineteness), and the Wilson-Hilferty transformation of gamma variables. Furthermore, the package provides interfaces to C code callable by another C code from other R packages.

Maintained by Felipe Osorio. Last updated 1 years ago.

commutation-matrix jarque-bera-test ldl-factorization lu-factorization matrix-api-for-r-packages matrix-norms modified-cholesky ols-regression power-method ridge-regression sherman-morrison statistics sweep-operator symmetrizer-matrix fortran openblas

19 stars 6.37 score 37 scripts 11 dependents

ayrangi

WaveletComp:Computational Wavelet Analysis

Wavelet analysis and reconstruction of time series, cross-wavelets and phase-difference (with filtering options), significance with simulation algorithms.

Maintained by Angi Roesch. Last updated 7 years ago.

5 stars 5.39 score 181 scripts 5 dependents

friendly

genridge:Generalized Ridge Trace Plots for Ridge Regression

The genridge package introduces generalizations of the standard univariate ridge trace plot used in ridge regression and related methods. These graphical methods show both bias (actually, shrinkage) and precision, by plotting the covariance ellipsoids of the estimated coefficients, rather than just the estimates themselves. 2D and 3D plotting methods are provided, both in the space of the predictor variables and in the transformed space of the PCA/SVD of the predictors.

Maintained by Michael Friendly. Last updated 4 months ago.

bias-variance graphics principal-component-analysis regression-models ridge-regression singular-value-decomposition

4 stars 4.84 score 69 scripts

techtonique

ahead:Time Series Forecasting with uncertainty quantification

Univariate and multivariate time series forecasting with uncertainty quantification.

Maintained by T. Moudiki. Last updated 1 months ago.

forecasting machine-learning predictive-modeling statistical-learning time-series time-series-forecasting uncertainty-quantification cpp

21 stars 4.63 score 51 scripts

aalfons

perryExamples:Examples for Integrating Prediction Error Estimation into Regression Models

Examples for integrating package 'perry' for prediction error estimation into regression models.

Maintained by Andreas Alfons. Last updated 3 years ago.

2.70 score

doufu1402

ProxReg:Linear Models for Prediction and Classification using Proximal Operators

Implements optimization techniques for Lasso regression, R.Tibshirani(1996)<doi:10.1111/j.2517-6161.1996.tb02080.x> using Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) and Iterative Shrinkage-Thresholding Algorithm (ISTA) based on proximal operators, A.Beck(2009)<doi:10.1137/080716542>. The package is useful for high-dimensional regression problems and includes cross-validation procedures to select optimal penalty parameters.

Maintained by YingHong Chen. Last updated 14 days ago.

2.00 score

cran

leapp:Latent Effect Adjustment After Primary Projection

These functions take a gene expression value matrix, a primary covariate vector, an additional known covariates matrix. A two stage analysis is applied to counter the effects of latent variables on the rankings of hypotheses. The estimation and adjustment of latent effects are proposed by Sun, Zhang and Owen (2011). "leapp" is developed in the context of microarray experiments, but may be used as a general tool for high throughput data sets where dependence may be involved.

Maintained by Yunting Sun. Last updated 3 years ago.

1.00 score