Discrete triangular distributions and non-parametric estimation for probability mass function

Discrete triangular distributions and non-parametric estimation for probability mass function

Non-parametric Estimation of Probability Distributions from Sampled Signals

This paper is concerned with the non-parametric estimation of probability distributions from band-limited and at least critically sampled signals such as images. Conventional approaches employing histograms or Parzen windows often perform unsatisfactorily since they ignore two important properties of such signals, namely that they are ordered and contain sufficient information to reconstruct th...

Parametric probability distributions

In this paper, we present an overview of basic parametric probability distributions which are frequently used in reliability. We present some main characteristics of these distributions, and briefly discuss underlying assumptions related to their suitability as models for specific reliability scenarios.

A New Weighted Information Generating Function for Discrete Probability Distributions

The object of this paper is to introduce a new weighted information generating function whose derivative at point 1 gives some well known measures of information. Some properties and particular cases of the proposed generating function have also been studied.

Parametric Probability Distributions for Anomalous Change Detection

The problem of anomalous change detection arises when two (or possibly more) images are taken of the same scene, but at different times. The aim is to discount the “pervasive differences” that occur throughout the imagery, due to the inevitably different conditions under which the images were taken (caused, for instance, by differences in illumination, atmospheric conditions, sensor calibration...