Rank oriented models do not assume that we can exactly quantify the value of an alternative. They do not even assume that we know anything about the distribution of the utility, loss or other observable quantities characterizing an alternative’s utility. We only assume that we are able to rank the alternatives drawn. However the necessity to introduce search cost in our considerations seem to d...

In this paper, we propose a method for image clustering using multinomial mixture models. The mixture of multinomial distributions, often called multinomial mixture, is a probabilistic model mainly used for text mining. The effectiveness of multinomial distribution for text mining originates from the fact that words can be regarded as independently generated in the first approximation. In this ...

For a probability distribution (ps; s 2 S) on a nite set S, call a random forest F of rooted trees labeled by S (with edges directed away from the roots) a p-forest if given F has m edges the vector of out-degrees of vertices of F has a multinomial distribution with parameters m and (ps; s 2 S), and given also these out-degrees the distribution of F is uniform on all forests with the given out-...

We describe a general framework for testing neutral theory. We summarize similarities and differences between ten different versions of neutral theory. Two central predictions of neutral theory are that species abundance distributions will follow a zero-sum multinomial distribution and that community composition will change over space due to dispersal limitation. We review all published empiric...

Serial analysis of gene expression (SAGE) is a technology for quantifying gene expression in biological tissue that yields count data that can be modeled by a multinomial distribution with two characteristics: skewness in the relative frequencies and small sample size relative to the dimension. As a result of these characteristics, a given SAGE sample may fail to capture a large number of expre...