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Description
  • Tail behavior of robust and classical estimators in linear model and its relation to their breakdown point. Model with a random regresion matrix and the effect of the extreme values in the projection matrix on the least squares and other estimators with regards to the shape of the basic distribution of the errors. Regression quantiles, extreme regressio quantiles, and the statistical inference based on extreme regression quantiles. Tests of statistical hypotheses in linear regression and autoregression models, based on (auto)regression rank scores. (en)
  • Chováni chvostu rozdeleni pravdepodobností robustních i klasických odhadu v lineárním modelu a vztah k jejich bodu selháni. Modely s náhodnou regresní maticí a vliv extrémních hodnot projekcní matice na odhad metodou nejmenších ctvercu a na jiné odhady, s ohledem na tvar základního rozdelení pravdepodobností chyb. Regresní kvantily, extrémní regresní kvantily a statistická inference založená na extrémních regresních kvantilech. Testy statistických hypotéz v linearních regresních a autoregresních modelech, založené na (auto)regresních poradových skórech.
Title
  • Quantile regression (en)
  • Regrese založená na regresních kvantilech
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  • ME 381
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  • Tail behavior of regression estimators, breakdown point, random regresion matrix, maximal diagonal element of the hat matrix, regression quantiles, extreme regressio quantiles, regression rank scores (en)
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  • Nové odhady Paretova indexu, jeden je první v regresním modelu (cs)
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  • breakdown point
  • extreme regressio quantiles
  • maximal diagonal element of the hat matrix
  • random regresion matrix
  • regression quantiles
  • Tail behavior of regression estimators
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