Sentence examples for using the sample covariance from inspiring English sources

Using the sample covariance matrix of the complete data (39).

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.

Viewing p ̂ k | k - 1 ( t ) as the weighted average of G position-samples { g j } j = 1 G, it is straightforward to estimate the covariance of P ̂ k | k - 1 ( t ) using the sample covariance as P ̂ k | k - 1 ( t ) = ∑ j = 1 G x ̌ k | k - 1, t ( j ) g j - p ̂ k | k - 1 ( t ) g j - p ̂ k | k - 1 ( t ) T ∑ j = 1 G x ̌ k | k - 1, t ( j ).

The variance covariance matrix Σ of univariate test statistics using the sample covariance matrix of the test statistics of all SNPs from univariate GWAS analyses as an approximation.

Among the detectors currently available, a spatio-temporal adaptive detector which uses the sample covariance matrix estimate from secondary (signal free) data vectors is proposed in [1] and [2] by Brennan, Reed and Mallett.

In contrast, the low-dimensional vector computations used the sample covariance matrix explicitly.

For each patient, the starting scores on the four DAS-28 domains are computer generated by drawing at random from a multivariate normal distribution which was estimated using the sample means and covariance of the logit of the four domains.

The test statistic used is the sample covariance of the measurements between the two sensor nodes compared to a constant threshold γ c.

It has been shown [ 13] that provided the distances derived from sequences satisfy the maximum likelihood criterion, their distribution is approximately multivariate normal, which allows to estimate their variances and covariances using the sample average method [ 13].

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.

Using the conventional sample covariance matrix significantly degrades performance at short range.