Such problems arise in many practical contexts such as Telecommunications, logistic networks, power distribution networks, etc.
In this context, this paper reviews the role and applications of geo-spatial tool such as Geographical Information System (GIS) for precise agro-residue resource assessment, biomass logistic and power plant design.
Logistic regression power calculation was carried out using PASS software version 13.0.10 (NCSS statistical Software, Kaysville, UT).
These parameters were used as input for the mathematical model of the gasifier, furthermore they can influence the logistic of the power plant affecting the storage volumes [19].
We repeated the logistic regression and power analysis by selecting a 60% random subsample of the controls that results into similar sample size as that of the cases (results not presented), which yielded very similar results, qualitatively and quantitatively.
The relationships between OD, daily OD, PELOD, daily PELOD and mortality were compared between the two strata (neonates, older children) based on the discrimination power, logistic and multiple regression analyses.
Together with findings reported earlier [6], [17], [18], [26] regarding the conformance to the NBL for some survival distributions (exponential, Muth, Gompertz, Weibull, gamma, log-logistic, and exponential power distributions) our results indicate that the validity of the NBL requires that the frequency of 'natural' numbers in the sense of Newcomb [1] decreases with increasing magnitude.
The obtained model is defined as the logistic smooth transition asymmetric power GARCH model in which (delta) represents the asymmetric power parameter to be estimated by nonlinear least squares or maximum likelihood methods as in the APGARCH methodology of Conrad et al. (2010).
However, the multinomial regression model, which allows for heterogeneity of allelic effects between sub-phenotypes, has noticeably greater power than logistic regression analysis of all cases combined (MULTINOMIAL compared with LOGISTIC).
