We then modeled the number of mislaid eggs in: (1) one-egg clutches, (2) two-egg clutches, and (3) both one- and two-egg clutches as a function of total available nests using generalized linear mixed models (GLMM) that assumed a Poisson distribution
. We included an offset term in each model for the number of breeding females, which allowed us to assess the number of mislaid eggs relative to the number of females at each site.
Note that count data can be modelled for certain distributions using continuous distributions; for example, count data that follows a Poisson distribution
and has a high mean can be modelled using a normal distribution.
Traditionally, a macroscopic approach for analysing such networks have been used wherein the users and/or remote radio heads are randomly deployed, often following a homogeneous Poisson distribution
such that well established stochastic geometry theory can be applied.
* Conditional on the past [[U.bar].sub.t], variable [Z.sub.t] follows Poisson distribution
with parameter [[beta]U.sub.t].
In this paper, we highlight the use of neutrosophic crisp sets theory [3,4] with the classical probability distributions, particularly Poisson distribution
, Exponential distribution and Uniform distribution, which opens the way for dealing with issues that follow the classical distributions and at the same time contain data not specified accurately.
In real networks, the degree distribution P(k) , defined as the probability that a node chosen uniformly at random has degree k or, equivalently, as the fraction of nodes in the graph having degree k, significantly deviates from the poisson distribution
expected for a random graph  and, in many cases, exhibits a power law (scale-free) tail with an exponent .
The count data of each taxon was checked for fit to a known probability distribution according to the steps in Krebs (1999) and Crawley (2007): Poisson distribution
for random pattern (ID = 1), negative binomial distribution for aggregated pattern (ID > 1), and binomial distribution for uniform pattern (ID < 1).
In these cases, the latent variables follow, respectively, a geometric and a zero-truncated Poisson distribution
and each of components in risk came from a Weibull baseline distribution.
Examples are as follows: for p = 0 then we have a normal distribution, p = 1, and [THETA] = 1; it is a Poisson distribution
, and Gamma distribution for p = 2, while when p = 3 it is Gaussian inverse distribution.
Recently, Porwal  introduced a Poisson distribution
series whose coefficients are probabilities of Poisson distribution
and established a correlation between Statistics and Geometric Function Theory which opened up a new direction of research.
Regarding the fitting of the binomial distribution, if as n increases, p decreases such that n * p remains constant, then the binomial distribution approaches the Poisson distribution
; see Mood, Graybill, and Boes (1974).
was employed to analyze lowest-detectable copy range.