Sentence examples for binomial function in which from inspiring English sources

When k is 1, this simplifies to Equation 2. (1) f (k + ; n ; p ) = 1 − ∑ i = 0 i < k (n i ) p i (1 − p ) n − i (2) f (1 + ; n ; p ) = 1 − (1 − p ) n SLiMChance uses three cycles of the binomial function in which the probability calculated becomes P for the next calculation (Table 1).

Measures of association are presented with 95% confidence intervals calculated by use of the binomial function in the STATA statistical software version 12.

We compared the difference in visitation frequency of each visitor species by constructing a GLM (binomial error, logit-link function), in which bract treatment, year and their interaction were treated as fixed factors.

The binomial denominator and dispersion parameters were 1. Changes to infection loads during the course of the experiment, were analysed using a GLMM with Poisson error structure and log-link function in which load size (numbers of BdGE) was fitted as the response term.

For example, more robust diagnostic accuracy information, especially at higher levels of the AUDIT scale, might produce a better and more appropriate fit than the negative binomial function used in this analysis, which could have an effect on the calculated post-test probabilities.

We also performed a mixed-model analysis using the glmer function in the R package lme4 (Bates, 2010) with a logit link function and a binomial error structure, in which all effects except the number of adults were specified as random.

In that paper, the author studies the evaluation of the generalized expected penalty function in the compound binomial risk model in which the premium rate received per period is c ((cinmathbb{N}^)).

This gives rise to the negative binomial (NB) distribution in which the variance increases as a quadratic function of the mean, i.e., Var y) = μ + φμ[ 7].

We conclude that the zero-inflated negative binomial (ZINB) model, in which the parent distribution is specified to follow a negative binomial distribution as in equation (6), is the best fit for our data.

Test for non-randomness: The probability that at least x IS elements will end up in a certain segment of the genome was computed with the binomial probability density function, which is used to find the probability of at least x successes out of n trials, given the probability p for success.

In this work, the fuzzy extension of the binomial function and the Gaussian function were used [ 58].