Frank R. Hampel – författare
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5 produkter
Robust Statistics
The Approach Based on Influence Functions
Av Frank R. Hampel, Elvezio M. Ronchetti m. fl.
Häftad, 2005
1843 kr
Lägg i varukorg
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to …
Robust Estimates of Location
Survey and Advances
Av David F. Andrews, Frank R. Hampel
Häftad, 2015
1420 kr
Lägg i varukorg
Because estimation involves inferring information about an unknown quantity on the basis of available data, the selection of an estimator is influenced by its ability to perform well under the conditions that are assumed to underlie the data. Since these conditions are never known exactly, the …
Robust Estimates of Location
Survey and Advances
Av David F. Andrews, Frank R. Hampel
Inbunden, 2016
3299 kr
Lägg i varukorg
Because estimation involves inferring information about an unknown quantity on the basis of available data, the selection of an estimator is influenced by its ability to perform well under the conditions that are assumed to underlie the data. Since these conditions are never known exactly, the …
Robust Statistics
The Approach Based on Influence Functions
Av Werner A. Stahel, Peter J. Rousseeuw m. fl.
E-bok, 2011
2590 kr
Lägg i varukorg
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to …
Robust Estimates of Location
Survey and Advances
Av Frank R. Hampel, David F. Andrews
E-bok, 2015
1113 kr
Lägg i varukorg
Because estimation involves inferring information about an unknown quantity on the basis of available data, the selection of an estimator is influenced by its ability to perform well under the conditions that are assumed to underlie the data. Since these conditions are never known exactly, the …
