Objective The specific mortality rate (MR) due to COVID-19 is a useful indicator for monitoring and evaluating the health strategies of systems in pandemic era. main objective this study estimate effects social, health, economic factors on MRs 176 countries. Material Methods Beta regression models were used, estimated as total number deaths divided by confirmed cases (infection fatality rate) u...

Abstract I propose a new model, ordered Beta regression, for continuous distributions with both lower and upper bounds, such as data arising from survey slider scales, visual analog dose–response relationships. This model employs the cut point technique popularized by logit to fit single linear (0,1) degenerate [0,1] responses. The can be estimated or without observations at is general solution...

This paper proposes predictive inference for the multiple regression model with independent normal errors. The distributions of the sample regression vector (SRV) and the residual sum of squares (RSS) for the model are derived by using invariant differentials. Also the predictive distributions of the future regression vector (FRV) and the future residual sum of squares (FRSS) for the future reg...

Motivated by the recent popularization of beta prime distribution, a more flexible generalization is presented to fit symmetrical or asymmetrical and bimodal data, non-monotonic failure rate. Thus, Weibull-beta distribution defined, some its structural properties are obtained. The parameters estimated maximum likelihood, new regression model proposed. Some simulations reveal that estimators con...

The CAPM model assumes stock returns to be a linear function of the market return. However, there is considerable evidence that the beta stability assumption commonly used when estimating the model is invalid. Nonparametric regression methods are used to examine the stability of beta coefficients in German stock returns. Since local polynomial regression is used for estimation, known methods fo...

Finite mixture models have come to play a very prominent role in modelling data. The finite mixture model is predicated on the assumption that distinct latent groups exist in the population. The finite mixture model therefore is based on a categorical latent variable that distinguishes the different groups. Often in practice distinct sub-populations do not actually exist. For example, disease s...