Oszacowania błędów estymatorów stosowanych w markowowskich metodach Monte Carlo
نویسنده
چکیده
W wielu modelach statystyki bayesowskiej kluczowym problemem jest obliczanie całek względem rozkładów a posteriori, które są skomplikowane i możliwe jest jedynie wyznaczenie ich gęstości z dokładnością do stałej normującej. W tej sytuacji najczęściej stosowanym i bardzo skutecznym narzędziem są markowowskie metody Monte Carlo (Markov Chain Monte Carlo, MCMC). Jest to rodzina algorytmów, które pozwalają wyznaczyć przybliżone wartości całki
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