A. Azzalini's Inferenza statistica, una presentazione basata sul concetto PDF

By A. Azzalini

ISBN-10: 0195159888

ISBN-13: 9780195159882

Il concetto di verosimiglianza gioca un ruolo fondamentale nell'impostazione corrente della Statistica, sia according to introdurre nozioni generali della teoria che consistent with lo sviluppo di metodi specifici. Questo libro presenta un'esposizione della teoria statistica basata sulla verosimiglianza, osservata dal punto di vista della "teoria classica", e dimostra come il corpo principale delle tecniche statistiche attualmente in uso possano essere desunte da un numero limitato di concetti-chiave. L'attuale edizione integra los angeles precedente con un capitolo sui modelli lineari generalizzati e con altri aggiornamenti quali numerose illustrazioni numeriche, basate su applicazioni reali, che facilitano l. a. percezione della rilevanza operativa dei metodi presentati.

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Sample text

The center dashed line is the result of the linear regression; the center horizontal line, assuming constant radiation intensity, stands for the mean value ym . The corresponding lines above and below these alternative best estimates indicate the 1σ confidence intervals not necessarily the best approximation to the true value (see the example in Sect. 3). Note the example in Sect. 2 of how significantly just one (isolated) data point influences a least-squares result. It should also be clear that even widely differing parameter pairs (a0 , a1 ) could deliver very similar data values if the range of interest is very limited.

3). Let us assume that in a set of ten data points there is one data point with a deviation of 4 standard deviations. 8 × 103 points would. This factor equals the ratio of the numbers of data points used in the comparison; this can be deduced from the definition of the mean value given in Sect. 1. Thus the best estimate would be overly influenced by the value of the outlier, so it is worthwhile to check this outlying value thoroughly. If there is an outlier there are two possibilities: • The model is wrong– after all, a theory is the basis on which we decide whether a data point is an outlier (an unexpected value) or not.

3. Calculate the mean value of the suspicious data point with appropriate other points and adjust the uncertainty of the combined value correspondingly. 4. Exclude the suspicious data point and document the fact that you have done this. 5. Keep the suspicious data point and learn to live with the discrepancy. , via computers, because we should always be aware of the steps taken. Discarding data is very critical. It is vital that any manipulation of data remains a rare exception and that it is well documented.

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Inferenza statistica, una presentazione basata sul concetto di verosimiglianza by A. Azzalini


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