The optimal cost distribution of raw materials (namely "generalized optimal construct") is obtained.
The optimal distribution of each raw material cost in the total cost, namely "generalized optimal construct", is obtained.
To further assess which model best suits our data, we compare the Akaike's information criterion (AIC) values of several models, namely Poisson, negative binomial, generalized Poisson, generalized negative binomial, zero-inflated Poisson and zero-inflated negative binomial.
Theoretical results and their implications are demonstrated by examining specific problems, namely: Generalized encoding schemes, accounting for the coding structure of the primary user; Simple outer bounds on rate regions; Capacity of the cognitive setting in the degraded message set case; Results for a class of Z-channels and Cognitive Wyner based cellular models.
Two numerical solution alternatives are investigated, namely Generalized Reduced Gradient (GRG2) and evolutionary algorithm.
Applications of the stochastic models, namely data assimilation, are presented.
Observational data on mean annual ground temperature (MAGT) and active layer thickness (ALT), together with geospatial data, were used to calibrate statistical models using generalized linear models (GLM), generalized additive models (GAM), random forest (RF) and generalized boosted models (GBM).
Logistic regression, generalized linear models and generalized mixed models.
Third, the CPBA model naturally generalizes network approximations that are already part of scientific practice, namely, the propensity based approach in multigraph models, the conformity decomposition in weighted networks, and the eigenvector based approximation in correlation networks.
The model generalizes the most popular model MEC and the recent model MFC.
