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  • Derivation of conditions for the consistency and asymptotic normality of M-estimators whose rho-functions are finite linear combinations of conves functions, which are practically verifiable in general statistical models with independent observations, including the linear and nonlinear regression, generalized linear models and proportional hazards models. Extension of these conditions to important types of observations on random fields. Application of the results in testing statistical hypotheses. (en)
  • Odvození podmínek pro konzistenci a asymptotickou normalitu M-odhadů, jejichž rho-funkce jsou konečnými lineárními kombinacemi konvexních funkcí, které jsou prakticky ověřitelné v obecných statistických modelech s nezávislými pozorováními, včetně lineární a nelineární regrese, zobecněných lineárních modelů a modelů Coxova typu. Rozšíření těchto podmínek na významné modely náhodných polí. Aplikace získaných poznatků v oblasti testování statistických hypotéz.
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  • General asymptotic theory of M-estimators (en)
  • Obecná asymptotická teorie M-odhadů
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  • IAA1075101
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  • M-estimators; Minimum disparity estimators; Asymptotic theory of estimators; Goodness-of-fit testing; Testing of composite hypotheses (en)
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  • New universal conditions for the consistency and asymptotic normality of general M-estimators in general statistical models. New alternatives to score functions, related distances and statistical applications. (cs)
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  • Asymptotic theory of estimators
  • Goodness-of-fit testing
  • Minimum disparity estimators
  • M-estimators
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