Inference for grouped data with a truncated skew-Laplace distribution

Inference for grouped data with a truncated skew-Laplace distribution

The skew-Laplace distribution has been used for modelling particle size with point observations. In reality, the observations are truncated and grouped (rounded). This must be formally taken into account for accurate modelling, and it is shown how this leads to convenient closed-form expressions for the likelihood in this model. In a Bayesian framework, “noninformative” benchmark priors, which ...

Application of the Truncated Skew Laplace Probability Distribution in Maintenance System

Network Inference from Grouped Data

In medical research, economics, and the social sciences data frequently appear as subsets of a set of objects. Over the past century a number of descriptive statistics have been developed to construct network structure from such data. However, these measures lack a generating mechanism that links the inferred network structure to the observed groups. To address this issue, we propose a modelbas...

Inference for a Skew Normal Distribution Based on Progressively Type-II Censored Samples

In many industrial experiments involving lifetimes of machines or units, experiments have to be terminated early or the number of experiments must be limited due to a variety of circumstances (e.g. when expensive, etc.) the samples that arise from such experiments are called censored data. Cohen (1991) was one of the earliest to study a more general censoring scheme called progressive censor...

Inference with bivariate truncated data.

In this paper we build on previous work for estimation of the bivariate distribution of the time variables T1 and T2 when they are observable only on the condition that one of the time variables, say T1, is greater than (left-truncation) or less than (right truncation) some observed time variable C1. In this paper, we introduce several results based on the Influence Curve (which we derive in th...