Sentence examples for definite estimates from inspiring English sources

Further such estimators provide positive definite estimates also when some components of the data points have a small variance, or the data distribution has a kurtosis different from the Gaussian case.

Actually some of such variables have a very small variance; anyway our optimal double shrinkage estimator of the covariance matrices of the clusters guarantees positive definite estimates also in this situation, stabilizing thus the local Mahalanobis distances that we use in our procedure.

Therefore computatitnal complexisy of thardrocedure above quito plausibly depends on the sizes and the ranks of the homologivepanys, along with the indefiniteestimatesthe mesh.

Such covariance matrices are estimated via an optimal double shrinkage method, which provides positive definite estimates even in presence of a few data points, or of data having components with small variance.

Primary care records-based prevalence studies may provide more definite estimates of the true extent of the problem.

Hill and Thompson [ 4] demonstrated how this affected estimates of genetic covariance matrices and that it resulted in high probabilities of obtaining non-positive definite estimates.

Thus in our procedure from time to time new clusters will be formed, composed only by a few data points, not sufficient to obtain a positive definite estimate of the corresponding covariance matrix using the classical sample covariance estimator.

Let us first observe that when a new cluster is formed, it contains too few data points to obtain a positive definite estimate of the covariance matrix, using the sample covariance matrix, at least until (Nle p,) where N is the number of data in a cluster and p the data points dimension.

In addition, the approach has the added advantage that it produces a regularized and positive definite estimate.

In addition, we cannot have a definite estimate of its true incidence.

First, it is essential to determine an accurate and positive definite estimate R of the correlation matrix.