We argue in this paper that it is more feasible to use binary variables and logistic regression analyses in the assessments of AIDS incidents o or other similar researches in social science. Thus, even in measuring disease persistence we can reach solid and comprehensive results. Statistical...

The technologically intensive nature of the predictive maintenance (PdM) method restricts its use to companies with higher turnover. This research is aimed to propose a PdM model for an N-component repairable system by integrating non-homogeneous Poisson process (NHPP) models and a system...

This paper proposes a predictive maintenance policy using modified failure mode effect and criticality analysis (Mod-FMECA) technique. FMECA is used to identify failure modes, reasons, effects and criticality of the system (machine/plant) but in Mod-FMECA in addition to the analysis carried for...

Marketing mix modeling has existed for decades now. Everyone has been using it, some tapped its potential with enormous success while others are yet to see its true potential. Rapidly changing marketing environment, consumer dynamics and multi touch points have made it even more complex to get...

In this paper, we recognize that reigning econometric paradigms, do not provide a basis for understanding the complex economic behavioral processes and systems. To acknowledge this void, we borrow some of the key fundamental concepts of entropy methods, and non equilibrium physical systems...

The following document outlines a technique for pricing interest rate swaps in terms of the underlying asset exposures and the internal yield to maturity of the contract. Hence, you can use the Par Yield as opposed to the entire Zero Curve, since the Par Yield implicitly embeds the Curve at the...

In this paper, we develop a modified maximum likelihood (MML) estimator for the multiple linear regression model with underlying student t distribution. We obtain the closed form of the estimators, derive the asymptotic properties, and demonstrate that the MML estimator is more appropriate for...

Bayesian inference requires an analyst to set priors. Setting the right prior is crucial for precise forecasts. This paper analyzes how optimal prior changes when an economy is hit by a recession. For this task, an autoregressive distributed lag model is chosen. The results show that a sharp...