• glasso

  • Referenced in 412 articles [sw07432]
  • converged precision matrix might not be the inverse of the estimated covariance, and occasionally ... dual, the target of estimation is Σ, the covariance matrix, rather than the precision matrix...
  • spcov

  • Referenced in 36 articles [sw12271]
  • spcov: Sparse Estimation of a Covariance Matrix. Provides a covariance estimator for multivariate normal data ... Tibshirani, R. (2011), ”Sparse Estimation of a Covariance Matrix,” Biometrika...
  • sandwich

  • Referenced in 31 articles [sw04486]
  • package sandwich: Robust Covariance Matrix Estimators , Model-robust standard error estimators for cross-sectional, time...
  • MIXOR

  • Referenced in 26 articles [sw08990]
  • individuals. MIXOR uses marginal maximum likelihood estimation, utilizing a Fisher-scoring solution. For the scoring ... random-effects variance-covariance matrix is estimated, along with the effects of model covariates. Examples...
  • corpor

  • Referenced in 21 articles [sw09381]
  • James-Stein-type shrinkage estimator for the covariance matrix, with separate shrinkage for variances ... inferring the covariance matrix the package also provides shrinkage estimators for partial correlations and partial ... variances. The inverse of the covariance and correlation matrix can be efficiently computed, as well...
  • ROBPCA

  • Referenced in 67 articles [sw11592]
  • robust scatter matrix such as the minimum covariance determinant or an S-estimator ... combines projection pursuit ideas with robust scatter matrix estimation. ROBPCA yields more accurate estimates...
  • corpcor

  • Referenced in 11 articles [sw10199]
  • James-Stein-type shrinkage estimator for the covariance matrix, with separate shrinkage for variances ... inferring the covariance matrix the package also provides shrinkage estimators for partial correlations and partial ... variances. The inverse of the covariance and correlation matrix can be efficiently computed, as well...
  • BSSasymp

  • Referenced in 11 articles [sw16157]
  • Mixing and Unmixing Matrix Estimates. Functions to compute the asymptotic covariance matrices of mixing ... unmixing matrix estimates of the following blind source separation (BSS) methods: symmetric and squared symmetric ... symmetric SOBI. Also functions to estimate these covariances based on data are available...
  • MIXNO

  • Referenced in 9 articles [sw10546]
  • data. MIXNO uses marginal maximum likelihood estimation, utilizing a Fisher-scoring solution. For the scoring ... random-effects variance-covariance matrix is estimated along with the (fixed) effects of explanatory variables...
  • FarmTest

  • Referenced in 5 articles [sw31555]
  • with fast data-drive tuning schemes to estimate model parameters and construct test statistics that ... that compute adaptive Huber mean and covariance matrix estimators that are of independent interest...
  • EASY - FIT

  • Referenced in 9 articles [sw05976]
  • provides confidence intervals for estimated parameters, correlation and covariance matrix, identification of significance levels...
  • FLIPS

  • Referenced in 7 articles [sw00299]
  • error. Usually, the measurement and the theory matrix are given and some statistical information about ... posteriori estimate (MAP estimate) and the posteriori covariance matrix of the unknown. If the error ... unknown, and the MAP estimate together with the posteriori covariance matrix are enough to determine...
  • EnKF-MC

  • Referenced in 2 articles [sw15209]
  • Modified Cholesky Decomposition for Inverse Covariance Matrix Estimation. This paper develops an efficient implementation ... modified Cholesky decomposition for inverse covariance matrix estimation. This implementation is named EnKF-MC. Background ... obtain sparse estimators of the inverse background error covariance matrix. The computational effort ... modified Cholesky for inverse covariance matrix estimation can reduce the impact of spurious correlations during...
  • clime

  • Referenced in 3 articles [sw25587]
  • Matrix Estimation. A robust constrained L1 minimization method for estimating a large sparse inverse covariance...
  • QuEST

  • Referenced in 6 articles [sw38788]
  • quest function. Certain estimation problems involving the covariance matrix in large dimensions are considered ... asymptotics. Recently, an estimator of the eigenvalues of the population covariance matrix has been proposed...
  • BIONJ

  • Referenced in 30 articles [sw08301]
  • these taxa, and reducing the distance matrix by replacing both taxa by this node. Moreover ... covariances of evolutionary distance estimates. This model is well adapted when these estimates are obtained ... minimizes the variance of the new distance matrix. In this way, we obtain better estimates...
  • ROCKET

  • Referenced in 11 articles [sw30016]
  • novel procedure for estimating parameters in the latent inverse covariance matrix. We establish asymptotic normality ... necessary for obtaining a (sqrt{n}) consistent estimator of an element in the precision matrix...
  • GHS

  • Referenced in 4 articles [sw37217]
  • develop a new estimator of the inverse covariance matrix for high-dimensional multivariate normal data ... proposed graphical horseshoe estimator has attractive properties compared to other popular estimators, such ... true inverse covariance matrix is sparse, the graphical horseshoe provides estimates with small information divergence...
  • QUIC

  • Referenced in 25 articles [sw11795]
  • regularized Gaussian maximum likelihood estimator (MLE) has been shown to have strong statistical ... guarantees in recovering a sparse inverse covariance matrix, or alternatively the underlying graph structure...
  • RidgeFusion

  • Referenced in 2 articles [sw27161]
  • implements ridge fusion methodology for inverse covariance matrix estimation for use in quadratic discriminant analysis ... clustering using ridge fusion for inverse matrix estimation, as well as tuning parameter selection functions ... have also implemented QDA using joint inverse covariance estimation...