Sentence examples for used the multinomial distribution from inspiring English sources

We first discretized the continuous features and then used the multinomial distribution to model their probabilities.

For the within-study model we used the multinomial distribution instead of the summary statistic approach usually followed in meta-analysis.

For P(X{ I  =  h }| I) we used the multinomial distribution method and Dirichlet prior as the Bayesian partition model in our study [ 20].

Since the data take the form of counts of discrete outcomes (1 to 5), we use the multinomial distribution.

This difference indicates that CIs that are valid when calculated using the multinomial distribution should also be valid in conditions where the hypergeometric distribution of sampling would be indicated.

As the data did not conform to simple variance assumptions implied in using the multinomial distribution, we used quasi-likelihood functions to compensate for the overdispersion of wasps within the olfactometer [ 29].

We use the multinomial distribution to compute the probability of observing every combination of bases (or residues) in the column according to the background distribution, and calculate the corresponding SP-score for the column.

The utility of the Monte Carlo approach is also somewhat unclear to me, as it appears that the expected CAI could be calculated analytically, along with confidence intervals, using the multinomial distribution.

Once the mixing proportions θ d are generated, for each transcript read to generate, we randomly select a source using the mixing proportions θ d, then randomly select a transcript from which to generate a read using the multinomial distribution specified by the expression profile of the chosen source.

For Simu 3, the number of cases for each of the 532 areas is generated using the multinomial distribution as follows: where N is the total number of cases in the study region and is set equal (to the nearest integer) to the sum of the expected counts across all 532 areas.

The method uses the density function of the multinomial distribution that provides the probability of an event that would have led to the number of reads observed for a given amplicon and for a given set of amplification efficiency values.