A number of previous studies have shown that a combination of forecasts typically outperforms any component forecast. Service managers may wish to use forecast combination to improve forecast accuracy in predicting retail sales. In this study, revenue data from an actual service company is used to generate and test a least absolute value (LAV) regression model for forecast combination. The LAV ...

A simple approach was developed to predict corn yields using the MoDerate Resolution Imaging Spectroradiometer (MODIS) data product from two geographically separate major corn crop production regions: Illinois, USA and Heilongjiang, China. The MOD09A1 data, which are eight-day interval surface reflectance data, were obtained from day of the year (DOY) 89 to 337 to calculate the leaf area index ...

In this paper, we develop and evaluate a Localization Anomaly Detection (LAD) scheme for non-flat surfaces for wireless sensor networks. The beacon-less grid localization scheme proposed for non-flat terrains in [1] is used for localization and the localization anomaly detection uses observations of the sensor node at two different reception ranges. Moreover, a new Signal Strength (SS) Metric i...

We deal with nonparametric estimation in a nonlinear cointegration model whose regressor and dependent variable can be contemporaneously correlated. The asymptotic properties of the Nadaraya-Watson estimator are already examined in the literature. In this paper, we consider nonparametric least absolute deviation (LAD) regression and derive the asymptotic distributions of the local constant and ...

Consider the random walk Gn:=gn…g1, n?1, where (gn)n?1 is a sequence of independent and identically distributed elements with law ? on general linear group GL(V) V=Rd. Under suitable conditions ?, we establish Cramér type moderate deviation expansions local limit theorems deviations for coefficients ?f,Gnv?, v?V f?V?. Our approach based Hölder regularity invariant measure Markov chain Gn?x=RGnv...

This paper discusses some asymptotic uniform linearity results of randomly weighted empirical processes based on long range dependent random variables+ These results are subsequently used to linearize nonlinear regression quantiles in a nonlinear regression model with long range dependent errors, where the design variables can be either random or nonrandom+ These, in turn, yield the limiting be...

We compare the results of measurements of the magnetic susceptibility (T), the linear coefficient of specific heat (T) C(T)/T , and 4 f occupation number n f(T) for the intermediate-valence compounds YbXCu4 (X Ag, Cd, In, Mg, Tl, Zn) to the predictions of the Anderson impurity model, calculated in the noncrossing approximation NCA . The crossover from the low temperature Fermi-liquid state to t...

We study large deviations principles for N random processes on the lattice Z d with finite time horizon [0, β] under a symmetrised measure where all initial and terminal points are uniformly given by a random permutation. That is, given a permutation σ of N elements and a vector (x1, . . . , xN ) of N initial points we let the random processes terminate in the points (xσ(1), . . . , xσ(N)) and ...

Theorem 1 in [2] is incorrect in the case α ≥ 1. Our error stems from the fact that the lower bound C 1 was determined by an integral expression which we treated as positive, whereas in fact it was zero. This led to an incorrect normalization A n when α ≥ 1. This error was communicated to us by K. Fleischmann and V. Wachtel, and the correction, that A n = p n 1 v (α−1) n for all 0 < α < ∞, appe...