Generalized thermoelastic models have been developed with the aim of eliminating the contradiction in the infinite velocity of heat propagation inherent in the classical dynamical coupled thermoelasticity theory. In these generalized models, the basic equations include thermal relaxation times and they are of hyperbolic type. Furthermore, Tzou established the dual-phase-lag heat conduction theo...

The main purpose of this paper is to estimate the volatility in global fertilizer prices. The endogenous structural breakpoint unit root test and alternative volatility models, including the generalized autoregressive conditional heteroskedasticity (GARCH) model, Exponential GARCH (EGARCH) model, and GJR model are estimated for six global fertilizer prices and the crude oil price. Weekly data f...

We consider compact Grassmann manifolds G/K over the real, complex or quaternionic numbers whose spherical functions are Heckman–Opdam polynomials of type BC. From an explicit integral representation of these polynomials we deduce a sharp Mehler–Heine formula, that is an approximation of the Heckman–Opdam polynomials in terms of Bessel functions, with a precise estimate on the error term. This ...

The empirical (sandwich or robust) covariance matrix, usually used in conjunction with Generalized Estimating Equations (GEE) and Generalized Linear Mixed Models (GLMM), is biased towards zero for small sample sizes. As a consequence of this bias Type I error rates are usually higher than the nominal levels. Several small sample bias corrections have been proposed in the literature. The purpose...

We aim at proposing a Generalized Linear Model (GLM) with binary dependent variable Y , whose link function defined by the Generalized Extreme Value (GEV) distribution. We define this model as GEV regression. The goal of this paper is to overcome the drawbacks shown by the logistic regression in rare events: the probability of rare events is underestimated and the logit link is a symmetric func...

Dan Zhang Leads School of Business, University of Colorado at Boulder, Boulder, CO 80309, USA [email protected] Inventory-based dynamic pricing has become a common operations strategy in practice and has received considerable attention from the research community. From an implementation perspective, it is desirable to design a simple policy like a base stock list price (BSLP) policy. The e...

It is often asserted that deep networks learn “features”, traditionally expressed by the activations of intermediate nodes. We explore an alternative concept by defining features as partial derivatives of model output with respect to model parameters—extending a simple yet powerful idea from generalized linear models. The resulting features are not equivalent to node activations, and we show th...

To obtain efficient estimation of parameters is a major objective in population pharmacokinetic study. In this paper, we propose an empirical likelihood-based method to analyze the population pharmacokinetic data based on the generalized linear model. A nonparametric version of the Wilk’s theorem for the limiting distributions of the empirical likelihood ratio is derived. Simulations are conduc...

Current opinion regarding the selection of link function in binary response models is that the probit and logit links give essentially similar results. This seems to be true for univariate binary response models; however, for multivariate binary response models such advice is misleading. We address a gap in the literature by empirically examining the relationship between link function selection...