Free BookThe Jackknife and Bootstrap (Springer Series in Statistics)

[Read.iBfc] The Jackknife and Bootstrap (Springer Series in Statistics)

[Read.iBfc] The Jackknife and Bootstrap (Springer Series in Statistics)

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The jackknife and bootstrap are the most popular data-resampling meth­ ods used in statistical analysis. The resampling methods replace theoreti­ cal derivations required in applying traditional methods (such as substitu­ tion and linearization) in statistical analysis by repeatedly resampling the original data and making inferences from the resamples. Because of the availability of inexpensive and fast computing, these computer-intensive methods have caught on very rapidly in recent years and are particularly appreciated by applied statisticians. The primary aims of this book are (1) to provide a systematic introduction to the theory of the jackknife, the bootstrap, and other resampling methods developed in the last twenty years; (2) to provide a guide for applied statisticians: practitioners often use (or misuse) the resampling methods in situations where no theoretical confirmation has been made; and (3) to stimulate the use of the jackknife and bootstrap and further devel­ opments of the resampling methods. The theoretical properties of the jackknife and bootstrap methods are studied in this book in an asymptotic framework. Theorems are illustrated by examples. Finite sample properties of the jackknife and bootstrap are mostly investigated by examples and/or empirical simulation studies. In addition to the theory for the jackknife and bootstrap methods in problems with independent and identically distributed (Li.d.) data, we try to cover, as much as we can, the applications of the jackknife and bootstrap in various complicated non-Li.d. data problems. Why every statistician should know about cross-validation ... Great post Professor I am a little surprised that for time series (or dependent data in general) you did not mention the pertinent reference Dr. Arsham's Statistics Site - home.ubalt.edu The Birth of Probability and Statistics The original idea of"statistics" was the collection of information about and for the"state". The word statistics derives ... Bootstrap Methods: Another Look at the Jackknife - Springer Barnard. G. (1974) Conditionality. pivotals and robust estimation. Proceedings of the Conference on Foundational Questions in Statistical Inference. Multivariate statistics - Wikipedia Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable. Founders of statistics - Wikipedia Founders of departments of statistics. The role of a department of statistics is discussed in a 1949 article by Harold Hotelling which helped to spur the creation of ...
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