although knowing the time of the occurrence of the earthquakes is vital and helpful, unfortunately it is still unpredictable. by the way there is an urgent need to find a method to foresee this catastrophic event. there are a lot of methods for forecasting the time of earthquake occurrence. another method for predicting that is to know probability density function of time interval between earth...

Although knowing the time of the occurrence of the earthquakes is vital and helpful, unfortunately it is still unpredictable. By the way there is an urgent need to find a method to foresee this catastrophic event. There are a lot of methods for forecasting the time of earthquake occurrence. Another method for predicting that is to know probability density function of time interval between earth...

although there exist advanced models which predict beach profile for natural beaches, the behavior of the beaches in front of seawalls still suffers from the lack of appropriate theoretical models and sufficient measured data. in this paper, following the results obtained from the measurements, a beach profile evolution model is developed, using the measured probability distribution of the near...

 The ratio of independent random variables arises in many applied problems. In this article, the distribution of the ratio X/Y is studied, when X and Y are independent Rice random variables. Ratios of such random variable have extensive applications in the analysis of noises of communication systems. The exact forms of probability density function (PDF), cumulative distribution function (CDF) a...

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...

We consider a sequence of independent and identicaly distributed (iid) random variables with absolutely continuous distribution function F(x) and probability density function (pdf) f(x). Let Rnl be the largest observation after observing nth record and R(ns) be the smallest observation after observing the nth record. Then we say Wnr = Rnl− R(ns), n > 1, as the nth record range. We will c...

An argument of common probability density function (pdf) is generally a real number, which describes the density, or mass in case of discrete random variable, of a random variable. However, in some applications, the pdf can be a complex function, so called complex probability density function. This kind of pdf is then, as general complex function, characterized by the amplitude and phase and is...