In Probabilistic Logic Nilsson uses the device of a probability distribution over a set of possible worlds to assign probabilities to the sentences of a logical language. In his paper Nilsson concen­ trated on inference and associated computational issues. This paper, on the other hand, exam­ ines the probabilistic semantics in more detail, .particularly for the case of first order languages, a...

to belong to the graphical model. This direction was emphasized, for example, by Pearl (1988) and Geiger We formulate necessary and sufficient conditions for and Pearl (1993). Lauritzen (1996, Chapter 3) coman arbitrary discrete probability distribution to facpared these approaches and herein we extend his retor according to an undirected graphical model, or sults. a log-linear model, or other ...

Continuous probability distributions are widely used to mathematically describe random phenomena in engineering and physical sciences. In this paper, we present a methodology that can be used to formalize any continuous random variable for which the inverse of the cumulative distribution function can be expressed in a closed mathematical form. Our methodology is primarily based on the Standard ...

Before continuing, we will explain the terms probability, independent, and mutually exclusive events as this will assist in the understanding of the paper. The probability of an event is the proportion of times an event will occur if the experiment is repeated infinitely. These probabilities lie between 0 and 1, and an event with probability 0 will never occur, while an event with probability 1...

We study the problem of quantization of discrete probability distributions, arising in universal coding, as well as other applications. We show, that in many situations this problem can be reduced to the covering problem for the unit simplex. Such setting yields precise asymptotic characterization in the high-rate regime. Our main contribution is a simple and asymptotically optimal algorithm fo...

Sometimes input probability distributions for stochastic models are not so simple that standard distributions suit. In this case, we model with weighted sums of standard distributions. These composed distributions may have many parameters which must be estimated. This is not easy with common estimation methods like maximum-likelihood. We use the genetic algorithm for that. The design of the com...

If we want to assign probabilities to an event, and see no reason for one outcome to occur more often than any other, then the events are assigned equal probabilities. This is called the principle of insufficient reason, or principle of indifference, and goes back to Laplace. If we happen to know (or learn) something about the non-uniformity of the outcomes, how should the assignment of probabi...

statistical frequency analysis is the most common procedure for the analysis of flood data at a gauged location thatin first step it is needed to select a model to represent the population. among them, the central moment has been themost common and widely used, and with the using of computers, the application of the maximum likelihood hasincreased. this research was carried out in order to reco...