Wang, G. C. S., & Akabay, C. K. (1995). Autocorrelation: Problems and Solutions in Regression Modeling. Journal of Business Forecasting Winter 1994-95:18-26.Wang, George C. S. and Charles K. Akabay, "Autocorrelation: Problems and Solution in Regression Modeling," The Journal of ...
Atkinson PM, Aplin P, Curran PJ (1999) Per-field classification of land use using the forthcoming very fine spatial resolution satellite sensors: problems and potential solutions. In: Advanced in remote sensing and GIS analysis. Wiley, New York, pp 219–240 Atkinson PM, Curran PJ (1997) Ch...
For example, researchers have found ways to solve as SDPs some problems in control for which analytical solutions do not exist. However, the techniques used to formulate a problem as an SDP often result in the introduction of large numbers of auxiliary variables. This has an important ...
(2017). The spatial autocorrelation problem in spatial interaction modelling: a comparison of two common solutions. Letters in Spatial and Resource Sciences, 10 (1), 75-86.Griffith D A, Fischer M M, LeSage J P. The spatial auto- correlation problem in spatial interaction modeling: A ...
data: missing attribute value imputation (analogous to kriging); identifying colocations of local spatial autocorrelation hot spots and spatial medians; and, geographic tessellation stratified random sampling inputs to spatial optimization heuristics that successfully guide them to optimal location solutions....
It enabled researchers to assess statistically the degree of spatial dependence in their data and, in so doing, to search for more accurate solutions to their problems, including finding additionaldoi:10.1177/030913259501900205Getis, ArthurArthur Getis.Cliff, A.D. and Ord, J.K. 1973: Spatial ...
The first is the choice of kernel and bandwidth. The second is the well-known overrejection problem caused by strong serial correlation (or a possible unit root) in the errors.We provide solutions to both problems by using the fixed-basymptotic framework of Kiefer and Vogelsang (2005,...
sequences.The MF outperformed up to 24.335%and 2.708%against the state-of-the-art LABS heuristic algorithm,xLastovka,and Golay,respectively.These results indicated that the proposed algorithm's simulation had quality solutions in terms of fast convergence curve with better optimal means,and standard...
The algorithm uses the method of simulated annealing and is applied to a model data set. The algorithm is successful in finding solutions to both unconstrained and constrained maximum entropy problems.doi:10.1007/978-94-015-7860-8_16N. A. Farrow...