SUR models applied to an environmental situation with missing data and censored values.
Sparks, Ross (2004)
Journal of Applied Mathematics and Decision Sciences
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Sparks, Ross (2004)
Journal of Applied Mathematics and Decision Sciences
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Huang, Xingfang, Qiu, Peihua (2010)
Mathematical Problems in Engineering
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Tadeusz Bednarski (2016)
Discussiones Mathematicae Probability and Statistics
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Computationally attractive Fisher consistent robust estimation methods based on adaptive explanatory variables trimming are proposed for the logistic regression model. Results of a Monte Carlo experiment and a real data analysis show its good behavior for moderate sample sizes. The method is applicable when some distributional information about explanatory variables is available.
Jan Ámos Víšek (1992)
Kybernetika
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Konrad Furmańczyk (2014)
Applicationes Mathematicae
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The paper considers the problem of consistent variable selection in parametic models with the use of stepdown multiple hypothesis procedures. Our approach completes the results of Bunea et al. [J. Statist. Plann. Inference 136 (2006)]. A simulation study supports the results obtained.
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...
Erichsen, Lars, Brockhoff, Per Bruun (2004)
Journal of Applied Mathematics and Decision Sciences
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Sira Allende, Carlos Bouza, Isidro Romero (1995)
Qüestiió
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Robust estimation of the multiple regression is modeled by using a convex combination of Least Squares and Least Absolute Value criterions. A Bicriterion Parametric algorithm is developed for computing the corresponding estimates. The proposed procedure should be specially useful when outliers are expected. Its behavior is analyzed using some examples.
S. Luo, Shuxia Pang (2017)
Open Mathematics
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This paper studies quantile linear regression models with response data missing at random. A quantile empirical-likelihood-based method is proposed firstly to study a quantile linear regression model with response data missing at random. It follows that a class of quantile empirical log-likelihood ratios including quantile empirical likelihood ratio with complete-case data, weighted quantile empirical likelihood ratio and imputed quantile empirical likelihood ratio are defined for the...