Regression models for survival time data involve estimation of the hazard rate as a function predictor variables and associated slope parameters. An adaptive approach is formulated such regression modeling. The modeled using fractional polynomials, that is, linear combinations products power transforms together with other available predictors. These polynomial are restricted to generating posit...

This study implements the multivariable logistic regression to develop a credit scoring model based on tenants’ characteristics. The history of tenant is not considered. Rental information tenants was collected from landlord company in Malaysia. Parameters were estimated by using penalized maximum likelihood estimation with ridge since separation training data detected. initial factors consider...

The main purpose of this article is to introduce a new class regression models for bounded continuous data, commonly encountered in applied research. models, named the power logit assume that response variable follows distribution wide, flexible distributions with three parameters, namely, median, dispersion parameter and skewness parameter. offers comprehensive set tools likelihood inference d...

In this paper we investigate the flexibility of matrix distributions for modeling mortality. Starting from a simple Gompertz law, show how introduction matrix-valued parameters via inhomogeneous phase-type can lead to reasonably accurate and relatively parsimonious models mortality curves across entire lifespan. A particular feature proposed model framework is that it allows more direct interpr...

Topological indices are the real number of a molecular structure obtained via molecular graph G. Topological indices are used for QSPR, QSAR and structural design in chemistry, nanotechnology, and pharmacology. Moreover, physicochemical properties such as the boiling point, the enthalpy of vaporization, and stability can be estimated by QSAR/QSPR models. In this study, the QSPR (Quantitative St...

De-duplication Matlab's unique function was used for de-duplicating reviews – each row that appeared more than once was reduced to a single occurrence. This technique can produce some false positives in the case that the same word frequencies occurred in legitimately distinct reviews (since the order of the tokens is not considered), but the chances of this occurring was considered improbable e...