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010   $a1-280-25303-7
010   $a9786610253036
010   $a0-471-72537-4
010   $a0-471-72538-2
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100   $a19870323d1987      uy             0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aRobust regression and outlier detection$b[electronic resource] /$fPeter J. Rousseeuw, Annick M. Leroy
210   $aNew York $cWiley$dc1987
215   $a1 online resource (354 p.)
225 1 $aWiley series in probability and mathematical statistics. Applied probability and statistics,$x0271-6356
300   $aDescription based upon print version of record.
311   $a0-471-85233-3 
320   $aIncludes bibliographical references and index.
327   $aRobust Regression and Outlier Detection; Contents; 1. Introduction; 2. Simple Regression; 3. Multiple Regression; 4. The Special Case of One-Dimensional Location; 5. Algorithms; 6. Outlier Diagnostics; 7. Related Statistical Techniques; References; Table of Data Sets; Index; 
330   $aProvides an applications-oriented introduction to robust regression and outlier detection, emphasising °high-breakdown° methods which can cope with a sizeable fraction of contamination. Its self-contained treatment allows readers to skip the mathematical material which is concentrated in a few sections.
410  0$aWiley series in probability and mathematical statistics.$pApplied probability and statistics.
606   $aLeast squares
606   $aOutliers (Statistics)
606   $aRegression analysis
615  0$aLeast squares.
615  0$aOutliers (Statistics)
615  0$aRegression analysis.
676   $a519.5/36
700   $aRousseeuw$b Peter J$012084
701   $aLeroy$b Annick M$012085
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910830175803321
996   $aRobust regression and outlier detection$91143882
997   $aUNINA