co-channel interference is a major factor in limiting the capacity and link quality in cellular communications. as the co-channel interference is modeled by lognormal distribution, sum of the co-channel interferences of neighboring cells is represented by the sum of lognormal random variables (rvs) which has no closed-form expression. assuming independent, identically distributed (iid) rvs, the...

b a c k g r o u n d & aim: in many studies, the survival of patients with chronic kidney disease who are treated with peritoneal dialysis technique has been considered, while this is possible in peritoneal dialysis  patients  to switch  to another  treatment.  to achieve  more  accurate  estimation  of patient survival is necessary to examine all events. the purpose of this study is to estimate...

The uniformly minimum variance unbiased (UMVU), maximum likelihood, percentile (PC), least squares (LS) and weighted least squares (WLS) estimators of the probability density function (pdf) and cumulative distribution function are derived for the generalized Rayleigh distribution. This model can be used quite effectively in modelling strength data and also modeling general lifetime data. It has...

Tthe Zografos–Balakrishnan-log-logistic (ZBLL) distribution is a new distribution of three parameters that has been introduced by Ramos et el. [1], and They presented some properties of the new distribution such as its probability density function, The cumulative distribution function, The  moment generating function, its hazard (failure) rate function, quantiles and moments, Rényi and Shannon ...

We present an algorithm for computing the cumulative distribution function of the Kolmogorov{ Smirnov test statistic D n in the all-parameters-known case. Birnbaum (1952) gives an n-fold integral for the CDF of the test statistic which yields a function deened in a piecewise fashion, where each piece is a polynomial of degree n. Unfortunately, it is diicult to determine the appropriate limits o...

A smooth kernel estimator is proposed for multivariate cumulative distribution functions (cdf), extending the work of Yamato [H. Yamato, Uniform convergence of an estimator of a distribution function, Bull. Math. Statist. 15 (1973), pp. 69–78.] on univariate distribution function estimation. Under assumptions of strict stationarity and geometrically strong mixing, we establish that the proposed...