Sentence examples for measure representation of from inspiring English sources

The following theorem deals with a geometric measure representation of continuous star-shaped distributions.

To measure representation of abstract (numeric) magnitude, independent of any content-specific information, a series of line estimation tasks were given.

A geometric measure representation of the standardized p-power exponential law applies to show that this distribution is the p-generalized Fisher or F n,n (p -distribution.

This natural and easy Maurey-Rosenthal type theorem, which is a direct consequence of Theorem 4, can only be proved using the abstract setting of the vector measure representation of p-convex Banach lattices that has been shown in the previous section.

The representation index (RI) was used to measure representation of a motif in a set of sequences and was defined as the total number of occurrences of a motif (N) divided by the statistical expectation value (E) of the motif in a given set of sequences [ 44].

Along the same lines, Föllmer and Penner (2006) investigate the dynamic convex risk measures, representation of strong time consistency as a recursivity property, and they relate it to the Bellman principle of optimality.

We recall the geometric measure representation formula of Φ g,K (B) for every (B in mathfrak {B}^{n}), begin{array}{*{20}l} Phi_{g,mathbb{P}}(B &=C g,mathbb{P}) intlimits_{0}^{infty} r^{n-1}g(r) mathfrak{O}_{mathbb{S}}left left[ frac{1}{r}Bright] cap mathbb{S} right)dr =frac{1}{mathcal{I}(g)} intlimits_{0}^{infty} r^{n-1} g(r) mathfrak{F}_{mathbb{S}} B ,r drend{array} (8).

Selection-based techniques generally select notional conservation areas based on the surrogate, then measure representation, or likelihood of representation, of the test features in those areas [e.g. 24], [25], [28].

In this section we use the geometric measure representation formula (8) of multivariate polyhedral convex contoured probability distributions for simulating single values of this distribution by simulating the corresponding dgf g and the generalized uniform distribution (omega _{mathbb {S}}).

To this end, one might use various analytical tools like, e.g., a geometric measure representation as a starting point of explicit analytical derivations.

In all, these results suggest that there is little conservation of L1- and iL3 biased and -specific gene expression of S. ratti (measured by microarrays) and of S. stercoralis (measured by representation of ESTs in staged libraries).