Parametric and nonparametric empirical regression models: case study of copper bromide laser generation.
Gocheva-Ilieva, S.G., Iliev, I.P. (2010)
Mathematical Problems in Engineering
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Gocheva-Ilieva, S.G., Iliev, I.P. (2010)
Mathematical Problems in Engineering
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Meyer, Denny (1997)
Journal of Applied Mathematics and Decision Sciences
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Ham, Frederic M., Kostanic, Ivica (1996)
Mathematical Problems in Engineering
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Michal Haindl, Stanislava Šimberová (1998)
Kybernetika
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We present a new type of scratch removal algorithm based on a causal adaptive multidimensional prediction. The predictor use available information from the failed pixel surrounding due to spectral and spatial correlation of multispectral data but not any information from failed pixel itself. Predictor parameters cannot be directly identified so a special approximation is introduced.
Sparks, Ross (2004)
Journal of Applied Mathematics and Decision Sciences
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Robert Haining (1987)
Mathématiques et Sciences Humaines
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Silvie Bělašková, Eva Fišerová, Sylvia Krupičková (2013)
Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
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In most clinical studies, patients are observed for extended time periods to evaluate influences in treatment such as drug treatment, approaches to surgery, etc. The primary event in these studies is death, relapse, adverse drug reaction, or development of a new disease. The follow-up time may range from few weeks to many years. Although these studies are long term, the number of observed events is small. Longitudinal studies have increased the importance of statistical methods for time-to...
Ittig, Peter T. (2004)
Journal of Applied Mathematics and Decision Sciences
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Horng-Jinh Chang, Feng-Jenq Lin (1995)
The Yugoslav Journal of Operations Research
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Brenton R. Clarke, Antony G. Monaco (2004)
Discussiones Mathematicae Probability and Statistics
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In analysing a well known data set from the literature which can be thought of as a two-way layout it transpires that a robust adaptive regression approach for identifying outliers fails to be sensitive enough to detect the possible interchange of two observations. On the other hand if one takes the classical approach of diagnostic checking one may also stop too early and be satisfied with a model that falls short of a more detailed analysis that takes account of heteroscedasticity in...
S. Monira Sumi, M. Faisal Zaman, Hideo Hirose (2012)
International Journal of Applied Mathematics and Computer Science
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In the present article, an attempt is made to derive optimal data-driven machine learning methods for forecasting an average daily and monthly rainfall of the Fukuoka city in Japan. This comparative study is conducted concentrating on three aspects: modelling inputs, modelling methods and pre-processing techniques. A comparison between linear correlation analysis and average mutual information is made to find an optimal input technique. For the modelling of the rainfall, a novel hybrid...