Permutation Methods: A Distance Function Approach - ISBN:0387988823

Permutation Methods: A Distance Function Approach

Date: 28 April 2011, 08:33

Free register and download UseNet downloader, then you can FREE Download from UseNet.

Download without Limit " Permutation Methods: A Distance Function Approach " from UseNet for FREE!

Univariate and multivariate permutation methods are presented that provide exact probability values and approximate probability values based on resampling and moment techniques. Metric Euclidean distance functions are emphasized, in contrast to the nonmetric squared Euclidean distance functions common to statistical tests that rely on the assumption of normality. Permutation methods based on Euclidean distance yield powerful robust statistics for the detection of phenomena such as cyclic, autoregressive, and overly regular patterns, multiple clumping, and directional shifts of correlated data. The authors describe permutation methods associated with completely randomized and randomized block experimental designs. Applications of the distance function permutation approach include binary, and rank data. Type I error controlled regression analyses, including both prediction and linear models, are delineated. Because the regression analyses are based on a metric Euclidean distance function, special attention is paid to Least sum of Absolute Deviations (LAD) regression. Recently developed goodness-of-fit tests, measures of agreement, multidimensional contingency table tests, and multisample univariate permutation methods are discussed and compared.

Download Links:

Download Link (High Speed Download)

Download Link (http://www.space4upload.info/...showfile-62)

DISCLAIMER:

This site does not store Permutation Methods: A Distance Function Approach on its server. We only index and link to Permutation Methods: A Distance Function Approach provided by other sites. Please contact the content providers to delete Permutation Methods: A Distance Function Approach if any and email us, we'll remove relevant links or contents immediately.