Minimum Distance Estimation on Time Series Analysis With Little Data - Brossura

Tekin, Hakan

 
9781288327713: Minimum Distance Estimation on Time Series Analysis With Little Data
Brossura
ISBN 10: 1288327714 ISBN 13: 9781288327713
Casa editrice: British Library, Historical Print Editions, 2012

Sinossi

Minimum distance estimate is a statistical parameter estimate technique that selects model parameters that minimize a good-of-fit statistic. Minimum distance estimation has been demonstrated better standard approaches, including maximum likelihood estimators and least squares, in estimating statistical distribution parameters with very small data sets. This research applies minimum distance estimation to the task of making time series predictions with very few historical observations. In a Monte Carlo analysis, we test a variety of distance measures and report the results based on many different criteria. Our analysis tests the robustness of the approach by testing its ability to make predictions when the fitted time-series model does not match the data generation model. Our analysis indicates benefits in applying minimum distance estimation when making time series prediction based on less than 30 observations.

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Editore
British Library, Historical Print Editions
Data di pubblicazione
2012
Lingua
Inglese
ISBN 10 
1288327714
ISBN 13 
9781288327713
Rilegatura
Copertina flessibile
Numero di pagine
102
Contatto del produttore
non disponibile
Persona responsabile
gpsr@libri.de
gpsr@libri.de

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