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http://dbpedia.org/ontology/abstract Nella teoria della probabilità, una differNella teoria della probabilità, una differenza di martingala (in inglese: Martingale Difference Sequence (MDS)) è un processo stocastico caratterizzato da valore atteso condizionale nullo. In simboli, un processo stocastico è una differenza di martingala se vale la seguente condizione: Nel caso il valore atteso condizionale non dipenda, o non dipenda solo dalla storia passata della variabile, ma da un altro insieme di informazioni X, si dirà che il processo è una differenza di martingala condizionatamente ad X. Il nome della sequenza deriva dal fatto che questo particolare processo stocastico viene generato dalla differenza prima di una martingala. Da notare che, dall'ipotesi di valore condizionale nullo, discende l'assenza di autocorrelazione della serie.Si ha infatti: in cui e la seconda eguaglianza è un'applicazione della legge delle aspettative iterate. Da notare altresì che, nonostante le somiglianze, una differenza di martingala non è implicata e non implica un white noise. Infatti, se da un lato un white noise non necessariamente ha media condizionale nulla, dall'altro una differenza di martingala non richiede l'esistenza di un momento secondo (o varianza) finito.di un momento secondo (o varianza) finito. , In probability theory, a martingale differIn probability theory, a martingale difference sequence (MDS) is related to the concept of the martingale. A stochastic series X is an MDS if its expectation with respect to the past is zero. Formally, consider an adapted sequence on a probability space . is an MDS if it satisfies the following two conditions: , and, for all . By construction, this implies that if is a martingale, then will be an MDS—hence the name. The MDS is an extremely useful construct in modern probability theory because it implies much milder restrictions on the memory of the sequence than independence, yet most limit theorems that hold for an independent sequence will also hold for an MDS. A special case of MDS, denoted as {Xt,t}0 is known as innovative sequence of Sn; where Sn and are corresponding to random walk and filteration of the random processes . In probability theory innovation series is used to emphasize the generality of Doob representation. In signal processing the innovation series is used to introduce Kalman filter. The main differences of innovationterminologies are in the applications. The later application aims to introduce the nuance of samples to the model by random sampling.f samples to the model by random sampling.
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rdfs:comment In probability theory, a martingale differIn probability theory, a martingale difference sequence (MDS) is related to the concept of the martingale. A stochastic series X is an MDS if its expectation with respect to the past is zero. Formally, consider an adapted sequence on a probability space . is an MDS if it satisfies the following two conditions: , and, for all . By construction, this implies that if is a martingale, then will be an MDS—hence the name. A special case of MDS, denoted as {Xt,t}0 is known as innovative sequence of Sn; where Sn and are corresponding to random walk and filteration of the random processes . and filteration of the random processes . , Nella teoria della probabilità, una differNella teoria della probabilità, una differenza di martingala (in inglese: Martingale Difference Sequence (MDS)) è un processo stocastico caratterizzato da valore atteso condizionale nullo. In simboli, un processo stocastico è una differenza di martingala se vale la seguente condizione: Nel caso il valore atteso condizionale non dipenda, o non dipenda solo dalla storia passata della variabile, ma da un altro insieme di informazioni X, si dirà che il processo è una differenza di martingala condizionatamente ad X.enza di martingala condizionatamente ad X.
rdfs:label Martingale difference sequence , Differenza di martingala
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