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Description
  • From consistency results on estimators asymptotically minimizing a general criterion, we derive necessary and sufficient conditions for the convergence of approximate M-estimators in nonlinear regression models with nonstationary and/or dependent errors. Special attention is paid to models with errors satisfying the law of large numbers.
  • From consistency results on estimators asymptotically minimizing a general criterion, we derive necessary and sufficient conditions for the convergence of approximate M-estimators in nonlinear regression models with nonstationary and/or dependent errors. Special attention is paid to models with errors satisfying the law of large numbers. (en)
Title
  • Necessary and sufficient conditions for consistency of M-estimates in regression models with general errors.
  • Necessary and sufficient conditions for consistency of M-estimates in regression models with general errors. (en)
skos:prefLabel
  • Necessary and sufficient conditions for consistency of M-estimates in regression models with general errors.
  • Necessary and sufficient conditions for consistency of M-estimates in regression models with general errors. (en)
skos:notation
  • RIV/67985556:_____/00:16000098!RIV/2003/AV0/A16003/N
http://linked.open.../vavai/riv/strany
  • 243;267
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  • P(GA102/99/1137), Z(AV0Z1075907)
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  • 1/2
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  • 718814
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  • RIV/67985556:_____/00:16000098
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  • N/A (en)
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  • NL - Nizozemsko
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  • [CC98BA7B66F8]
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  • Journal of Statistical Planning and Inference
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  • 89
http://linked.open...iv/tvurceVysledku
  • Vajda, Igor
  • Liese, F.
  • Berlinet, A.
http://linked.open...n/vavai/riv/zamer
issn
  • 0378-3758
number of pages
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