LEADER 04802nam 22006734a 450 001 9910964232603321 005 20251116202705.0 010 $a9786611378981 010 $a9781281378989 010 $a1281378984 010 $a9789812774736 010 $a9812774734 035 $a(CKB)1000000000402037 035 $a(EBL)1681702 035 $a(OCoLC)879025573 035 $a(SSID)ssj0000236844 035 $a(PQKBManifestationID)11203241 035 $a(PQKBTitleCode)TC0000236844 035 $a(PQKBWorkID)10188189 035 $a(PQKB)11352553 035 $a(MiAaPQ)EBC1681702 035 $a(WSP)00005915 035 $a(Au-PeEL)EBL1681702 035 $a(CaPaEBR)ebr10201283 035 $a(CaONFJC)MIL137898 035 $a(Perlego)848210 035 $a(EXLCZ)991000000000402037 100 $a20050701d2006 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aResponse surface methodology and related topics /$feditor, Andre I. Khuri 205 $a1st ed. 210 $aHacenksack, N.J. $cWorld Scientific$dc2006 215 $a1 online resource (472 p.) 300 $aDescription based upon print version of record. 311 08$a9789812564580 311 08$a9812564586 320 $aIncludes bibliographical references and index. 327 $aContents ; Preface ; List of Contributors ; Chapter 1 Two-Level Factorial and Fractional Factorial Designs in Blocks of Size Two. Part 2 ; 1. Introduction ; 2. The Six Factor 64 Runs 26 Design ; 3. Definitions and Notation ; 4. Combination Design Selection Process 327 $a5. Case k = 6 d = 2 6. Case k = 6 d = 3 ; 7. Case k = 6 d = 4 ; 8. Case k = 6 d = 5 ; 9. Case k = 6 d = 6 ; 10. Sequential Designs for k = 7 Factors ; 11. Sequential Designs for k = 8 Factors ; References ; Chapter 2 Response Surface Experiments on Processes with High Variation 327 $a1. Introduction 2. Design Strategy ; 3. Choice of Size of Experiment ; 4. Choice of Treatments ; 5. Unit Structures ; 6. Multi-Stratum Designs ; 7. Data Analysis ; 8. Final Comments ; References 327 $aChapter 3 Random Run Order Randomization and Inadvertent Split-Plots in Response Surface Experiments 1. Introduction ; 2. Why Statistical Tests from RRO Experiments are Misleading ; 3. Examining the Split-Plotting Effect over All Randomizations 327 $a4. The Diagnostic Power to Retrospectively Detect the Randomization Restriction 5. The Expected Covariance Matrix for RRO Experiments ; 6. G-Efficiencies and Cost When an RRO is Used ; 7. Remarks ; References ; Chapter 4 Statistical Inference for Response Surface Optima 327 $a1. Introduction 330 $aThis is the first edited volume on response surface methodology (RSM). It contains 17 chapters written by leading experts in the field and covers a wide variety of topics ranging from areas in classical RSM to more recent modeling approaches within the framework of RSM, including the use of generalized linear models. Topics covering particular aspects of robust parameter design, response surface optimization, mixture experiments, and a variety of new graphical approaches in RSM are also included. The main purpose of this volume is to provide an overview of the key ideas that have shaped RSM, 606 $aResponse surfaces (Statistics) 615 0$aResponse surfaces (Statistics) 676 $a519.5 701 $aKhuri$b Andre? I.$f1940-$0251821 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910964232603321 996 $aResponse surface methodology and related topics$94534498 997 $aUNINA