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...

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...

 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...

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...

The aim of this paper is to define a new family of probability density functions (MR pdf) based on the multiresolution analysis theory. Each function of this family can be seen as a particular type of density mixture. The MR pdf has advantages of estimation over the conventional mixtures and it is suitable to model a large variety of square integrable probability density functions. The flexibil...

the probability density functions fitting to the discrete probability functions has always been needed, and very important. this paper is fitting the continuous curves which are probability density functions to the binomial probability functions, negative binomial geometrics, poisson and hypergeometric. the main key in these fittings is the use of the derivative concept and common differential ...

Density Estimation: Deals with the problem of estimating probability density functions (PDFs) based on some data sampled from the PDF. May use assumed forms of the distribution, parameterized in some way (parametric statistics); or May avoid making assumptions about the form of the PDF (nonparametric statistics). We are concerned more here with the non-parametric case (see Roger Barlow’s lectur...

The probability density functions fitting to the discrete probability functions has always been needed, and very important. This paper is fitting the continuous curves which are probability density functions to the binomial probability functions, negative binomial geometrics, poisson and hypergeometric. The main key in these fittings is the use of the derivative concept and common differential ...

Contents: Introduction. 1. The basic Gaussian Hidden Markov model. — 2. Some joint probability density functions of the process.-2.1. The joint pdf of (Y 1 , ..., Y T).-2.2. The joint pdf of the observations and one state of the Markov chain.-2.3. The joint pdf of the observations and two consecutive states of the Markov chain. — 3.