Sentence examples for value of a distribution from inspiring English sources

It is assumed here that at the level breakpoint from A to B the actual speed is very close to the desired (free) speed and one can calculate the variance value of speeds as the variance value of a distribution of desired (free) speeds.

In our method, we base the experimental design on the expected value of a distribution of variance reductions.

In our implementation we use two appearance features, φ1(p) the radius of p and φ2(p) the total intensity of p. The distances are normalized using the concept of a z-score (http://www.stats4students.com/Essentials/Standard-Score/Overview.php) wherein the measure is the number of standard deviations above or below the mean value of a distribution of 'raw' scores.

We can understand this by invoking the Fisher Tippett Gnedenko theorem for extreme (tail) values of a distribution.

In general, simple kriging does not closely reproduce the extreme values of a distribution with a gross thickness greater than 10 ft, observed in conditioning data.

The Anderson-Darling test has good power and is especially effective at detecting departure from normality in the high and low values of a distribution.

The former include simple linear regression (SLR), standardized precipitation index (SPI) and livelihood vulnerability index (LVI) supported with descriptive statistics such as mean, frequency counts, percentage, maximum and minimum values of a distribution.

In this case we use S i as discrete values of a distribution of selection coefficients on TAG stop codons in different genes in the same genome, while S 1 and S 2 were used as fixed values of the selection coefficients for all genes across a single genome.

In particular, we will consider how equality matters to the value of a social distribution; and whether a social distribution should respect Pareto optimality, the idea that if everyone prefers x to y then x is socially preferred to y.

Gamma support indicates the fractional support for a model including a gamma distribution of rates, and the shape parameter shows the α value of such a distribution.

For clustering distributions, the expected value of K r) is larger than the value of a random distribution, for regular patterns it is less than for a random distribution (examples are given in the Supplementary Material S1).