Weakly nonlinear constraints in regression models
Weakly nonlinear regression model with constraints I: nonlinear hypothesis
The problem considered is under which conditions in weakly nonlinear regression model with constraints I a weakly nonlinear hypothesis can be tested by linear methods. The aim of the paper is to find a region around the approximate value of the regression parameter with the following property. If we are certain that the actual value of the regression parameter is in this region, then the linear method of testing can be used without any significant deterioration of the inference.
Weighted Elastic Net Model for Mass Spectrometry Imaging Processing
In proteomics study, Imaging Mass Spectrometry (IMS) is an emerging and very promising new technique for protein analysis from intact biological tissues. Though it has shown great potential and is very promising for rapid mapping of protein localization and the detection of sizeable differences in protein expression, challenges remain in data processing due to the difficulty of high dimensionality and the fact that the number of input variables in...
When Product Type Experimental Design is Optimal? Brief Survey and New Results.
Why view and what is next?
N. N. Cencov wrote a commentary chapter included in the Appendix of the Russian translation of the Devroye and Györfi book [15] collecting some arguments supporting the view of density estimation. The Cencov’s work is available in Russian only and it hasn’t been translated, so late Igor Vajda decided to translate the Cencov’s paper and to add some remarks on the occasion of organizing the session “25 Years of the Density Estimation” at the Prague Stochastics 2010 Symposium. In this paper we...
Zur Bewertung von Schätzungen bei der gewöhnlichen Regressionsanalyse.
Zur Kondition des linearen Ausgleichsproblems mit linearen Gleichungen als Nebenbedingungen.
Zur Optimalität des F-Testes für lineare Hypothesen über lineare Modelle mit gemischten Effekten.
Асимптотические границы качества непараметрического оценивания регрессии в
Большие уклонения в линейной модели с мешающими параметрами
К теории оценивания параметров в схеме линейной регрессии
Непараметрическая оценка нелинейного функционала от регрессии при заданном плане
Новый подход к параметризации регрессионных зависимостей
О восстановлении распределения погрешностей в схеме линейной регрессии
Об одном применении модели двухфакторного дисперсионного анализа без взаимодействий
Об одном способе построения оптимальных планов эксперимента для круга
Об условии постоянства регрессии полиномиальной статистики на выборочное среднее