A Generalized Maximum Likelihood Characterization of the Normal Distribution.
Flow cytometry scatter are ofen used in microbiology, and their measures are related to bacteria size and granularity. We present an application of the skew-Laplace distribution to flow cytometry data. The goodness of fit is evaluated both graphically and numerically. We also study skewness and kurtosis values to assess usefulness of the skew-Laplace distribution.
Data that are proportions arise most frequently in biomedical research. In this paper, the exact distributions of R = X + Y and W = X/(X+Y) and the corresponding moment properties are derived when X and Y are proportions and arise from the most flexible bivariate beta distribution known to date. The associated estimation procedures are developed. Finally, two medical data sets are used to illustrate possible applications.
A characterization of geometric distribution is given, which is based on the ratio of the real and imaginary part of the characteristic function.
In this paper, we introduce a general family of continuous lifetime distributions by compounding any continuous distribution and the Poisson-Lindley distribution. It is more flexible than several recently introduced lifetime distributions. The failure rate functions of our family can be increasing, decreasing, bathtub shaped and unimodal shaped. Several properties of this family are investigated including shape characteristics of the probability density, moments, order statistics, (reversed) residual...
A new weighted version of the Gompertz distribution is introduced. It is noted that the model represents a mixture of classical Gompertz and second upper record value of Gompertz densities, and using a certain transformation it gives a new version of the two-parameter Lindley distribution. The model can be also regarded as a dual member of the log-Lindley- family. Various properties of the model are obtained, including hazard rate function, moments, moment generating function, quantile function,...
We describe a class of bivariate copulas having a fixed diagonal section. The obtained class contains both the Fréchet upper and lower bounds and it allows to describe non-trivial tail dependence coefficients along both the diagonals of the unit square.
The noncentral -distribution is a generalization of the Student’s-distribution. In this paper we suggest an alternative approach for computing the cumulative distribution function (CDF) of the noncentral-distribution which is based on a direct numerical integration of a well behaved function. With a double-precision arithmetic, the algorithm provides highly precise and fast evaluation of the extreme tail probabilities of the noncentral -distribution, even for large values of the noncentrality...