Titlebook: Parametric and Nonparametric Inference from Record-Breaking Data; Sneh Gulati,William J. Padgett Book 2003 Springer Science+Business Media

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Bayesian Models,s even more so. Even for the case of complete random samples, Bayesian inference can be quite complex and require highly sophisticated computational methods, such as Markov chain Monte Carlo, to obtain posterior distributions. It is not surprising then that very little research has been done on Baye

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Sneh Gulati,William J. Padgettmmter Produkte an saisonabhängige Unternehmen (z. B. Landwirtschaft, Spielwaren- oder Schmuckindustrie) gewährt wird. Der Saisonkredit ist ein sehr kurzfristiger Kredit und soll aus den Umsatzerlösen zurückgezahlt werden. (Self Liquidating Credit).

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Sneh Gulati,William J. Padgetteriving from the Balkans and attached to the Balkan Peninsula, the ‘balkanization’ discourse has gained a life of its own. The author challenges its current manifestations shaped by the era of social media and identifies and connects its meanings with deeper processes of historical events. This book

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Book 2003nd prediction about the underlying population parameters from both complete and incomplete data. Recently, methodology for estimation and prediction from incomplete data has been found useful for what is known as "record-breaking data," that is, data generated from setting new records. There has lon

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Parametric Inference,wever, statistical inference from record-breaking data remained virtually unexplored until the late 1970s when some statisticians started investigating the important and interesting problem of predicting future records.

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