Latent block models are used for probabilistic biclustering, which is shown to be an effective method analyzing various relational data sets. However, there has been no statistical test determining the row and column cluster numbers of latent models. Recent studies have constructed statistical-test-based methods stochastic models, assume that observed matrix a square symmetric assignments same ...

The influence of sample size on informetric characteristics is examined to determine whether theoretical mathematical models can adequately fit large data sets. Two large data sets of queries submitted to the Excite search service were sampled for search characteristics (term frequencies, terms used per query, pages viewed per query, queries submitted per session) producing data sets of various...

We propose a method to test for lack-of-fit of an estimated stochastic differential equation. The method is based on Monte Carlo simulation of trajectories between neighbour observations and, thus, it does not rely on the availability of explicit expressions of the conditional densities. Consequently, both non-linear models and models with state-dependent drift and diffusion can be handled. The...

One of the most important problems in time series analysis of stream flow and rainfall data in an area is selecting the best probability distribution. Since the rainfall stations are associated and correlated with each other, so statistical analysis of the station data seamlessly are very important. Therefore, the first step in data analysis, is selecting the prevailing probability distribution...

Abstract Various distribution free goodness-of-fit test procedures have been extracted from literature. We present two new binning free tests, the univariate three-region-test and the multivariate energy test. The power of the selected tests with respect to different slowly varying distortions of experimental distributions are investigated. None of the tests is optimum for all distortions. The ...