Sentence examples for the underlying random from inspiring English sources

Analytical expressions for the statistical properties of the underlying random processes are formulated.

A reality faced in the practical application of data processors is inexact statistical knowledge of the underlying random processes.

This is due to the nonidentical distribution of the underlying random processes and the correlation between the parameters.

These input models are often constructed from a set of experimental samples of the underlying random field.

The resultant probabilistic models assume that the underlying random variables, which define a measurable set of outcomes, can be defined independent of the measurement context.

The definition of an Integrated Mean-Squared Error (IMSE) criterion yields a particular Karhunen Loève expansion of the underlying random field.

Das and Mulder [ 27] first left the assumption that the true underlying random variable Y1 is normally distributed and considered arbitrary (usually unimodal) continuous distributions.

The model-based approach assumes that the value at each site is the realization of an underlying random process.

Second, we want to understand how many more coincident level crossings in a given time instance are expected if the underlying Gaussian random processes are correlated.

The traditional threshold model [ 4] postulates that there is an underlying random variable, called liability that follows a continuous distribution, and that the observed dichotomy is the result of the position of the liability with respect to a fixed threshold (t): phenotype = { 0   i f   λ < t 1   i f   λ ≥ t The liability is taken as the response variable.

In this analysis, we treat each measurement as a realization of an underlying random variable.