We study a model of non-Bayesian updating, based on the Hypothesis Testing model of Ortoleva (2012), for ambiguity averse agents. Agents ranks acts following the MaxMin Expected Utility model of Gilboa and Schmeidler (1989) and when they receive new information they update their set of priors as follows: If the information is such that all priors in the original set of priors assign to it a pro...

The Gaussian mixture probability density (GM-PHD) filter has become a popular approach to solve the multiple-target tracking (MTT) problem because it can effectively and efficiently estimate number of targets target states that change over time from noisy measurements. In GM-PHD filter, detection survival probabilities, birth rate are assumed be constant, irrespective state. However, in some ap...

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 ...

Based on recent studies by Guy Jumarie [1] which defines probability density of fractional order and fractional moments by using fractional calculus (fractional derivatives and fractional integration), this study expands the concept of probability density of fractional order by defining the fractional probability measure, which leads to a fractional probability theory parallel to the classical ...

Based on probability density evolution method (PDEM) and Bayes’ law, a new filter strategy is proposed, in which the prior of system state interest predicted by solving generalized equation (GDEE), posterior then updated terms Bayesian formula. Furthermore, Chebyshev polynomial-based collocation developed to obtain numerical solutions probability. Three illustrative examples are finally present...

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...

This report contains pseudo-code for, and a computational complexity analysis of, the Gaussian inverse Wishart Probability Hypothesis Density lter.