This paper presents a conditional mixture, maximum likelihood methodology for performing clusterwise linear regression. This new methodology simultaneously estimates separate regression functions and membership in K clusters or groups. A review of related procedures is discussed with an...

The clustering of their letter shapes is performed based on the pairwise distances between their topological signatures.The article presents a new probability distribution, created by compounding the Poisson distribution with the weighted exponential distribution. Important mathematical and...

This paper introduces Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data of unknown underlying distribution. The moments with conditional heteroscedasticity have been discussed. In a Monte Carlo experiment, it was found that the QML estimator performs as well as CLS and...

Easy to compute exact maximum likelihood estimators (MLEs) for parameters of a stochastic bivariate Itô Susceptible-Infected-Recovered (SIR) model and for parameters of an extension that treats undercounting are presented here

Maximum Likelihood (ML) shows both lower power and higher bias in small sample Monte Carlo experiments than Indirect Inference (II) and IIís higher power comes from its use of the model-restricted distribution of the auxiliary model coeffi cients (Le et al. 2016). We show here that IIís higher...