You might not bring for those books to somewhere you go. The author's research has been directed towards inference involving observables rather than parameters. In this book, he brings together his views on predictive or observable inference and its advantages over parametric inference.
While the book discusses a variety of approaches to prediction including those based on parametric, nonparametric, and nonstochastic statistical models, it is devoted mainly to predictive applications of the Bayesian approach.
It not only substitutes predictive analyses for parametric analyses, but it also presents predictive analyses that have no real parametric analogues. It demonstrates that predictive inference can be a critical component of even strict parametric inference when dealing with interim analyses. This approach to predictive inference will be of interest to statisticians, psychologists, econometricians, and sociologists.
I am sure all statisticians and students of statistics with an open mind will enjoy reading it and, hopefully will appreciate the beauty and usefulness of a coherent predictive view of their subject.
The monograph is addressed to statisticians and research workers who are intrested in the predictive approach. Its major contribution is likely to be as a resource for persons interested in trying predictive inference in some application.
In addition to publishing more than scholarly papers and reviews, Dr. Geisser was the Editor of four important volumes in statistical inference and applications, and the author of the unique and critically acclaimed book Predictive Inference.
Posting Komentar. Senin, 06 Februari [A Most helpful customer reviews See all customer reviews The comparison between the results of two phases clearly shows that the later phase i.
Experiments are carried out using reliable and real life historical meteorological data. The machine learning accuracy of solar radiation prediction is justified in terms of statistical error measurement and validation metrics.
Experimental results of this paper facilitate to make a concrete verdict that providing more attention and effort towards the feature subset selection and machine learning parameter optimization e. Follow Us.
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