Efficient Response Surface Designs for the Second-Order Multivariate Polynomial Model Robust to Missing Observation

Abstract Standard central composite design (CCD) originally requires that its factorial portion contains a full factorial design or fractional factorial design of resolution V or higher so that all effects of vital interest could be estimated. A CCD can be an ideal choice for lower number of factors...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Ahmad, Tanvir [verfasserIn] Akhtar, Munir

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2015

Schlagwörter:	Central composite designs Repaired resolution central composite designs Missing observations Minimax loss criterion

Anmerkung:	© Grace Scientific Publishing 2015

Übergeordnetes Werk:	Enthalten in: Journal of statistical theory and practice - Cham : Springer International Publishing, 2007, 9(2015), 2 vom: 01. Juni, Seite 361-375
Übergeordnetes Werk:	volume:9 ; year:2015 ; number:2 ; day:01 ; month:06 ; pages:361-375

Links:	Volltext

DOI / URN:	10.1080/15598608.2014.910479

Katalog-ID:	SPR038620316

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520			\|a Abstract Standard central composite design (CCD) originally requires that its factorial portion contains a full factorial design or fractional factorial design of resolution V or higher so that all effects of vital interest could be estimated. A CCD can be an ideal choice for lower number of factors (k). For k > 5, the standard CCD becomes very large and when, with the purpose of reduction of design size, the initial fractional factorial of resolution III or IV is used, the lower order effects are confounded. Block and Mee (2001) proposed some economical designs for k > 5. The designs were named as repaired resolution central composite (RRCC) designs; these actually repaired the portion containing factorial fractions of resolution III or IV. After repairing, the words of length four or lower were de-aliased and the effects of vital importance became estimable. In this study, some new versions of RRCC designs are constructed. All classes of designs are studied for their robustness to missing data. Loss of missing different kinds of design points has been computed.
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650		4	\|a Repaired resolution central composite designs \|7 (dpeaa)DE-He213
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650		4	\|a Minimax loss criterion \|7 (dpeaa)DE-He213
700	1		\|a Akhtar, Munir \|4 aut
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912			\|a GBV_ILN_32
912			\|a GBV_ILN_39
912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_90
912			\|a GBV_ILN_95
912			\|a GBV_ILN_100
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_120
912			\|a GBV_ILN_138
912			\|a GBV_ILN_150
912			\|a GBV_ILN_151
912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_171
912			\|a GBV_ILN_187
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_250
912			\|a GBV_ILN_266
912			\|a GBV_ILN_281
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_636
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2006
912			\|a GBV_ILN_2007
912			\|a GBV_ILN_2008
912			\|a GBV_ILN_2009
912			\|a GBV_ILN_2010
912			\|a GBV_ILN_2011
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2020
912			\|a GBV_ILN_2021
912			\|a GBV_ILN_2025
912			\|a GBV_ILN_2026
912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2031
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2037
912			\|a GBV_ILN_2038
912			\|a GBV_ILN_2039
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2057
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2093
912			\|a GBV_ILN_2106
912			\|a GBV_ILN_2107
912			\|a GBV_ILN_2108
912			\|a GBV_ILN_2110
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2118
912			\|a GBV_ILN_2129
912			\|a GBV_ILN_2143
912			\|a GBV_ILN_2144
912			\|a GBV_ILN_2147
912			\|a GBV_ILN_2148
912			\|a GBV_ILN_2152
912			\|a GBV_ILN_2153
912			\|a GBV_ILN_2188
912			\|a GBV_ILN_2190
912			\|a GBV_ILN_2232
912			\|a GBV_ILN_2336
912			\|a GBV_ILN_2446
912			\|a GBV_ILN_2470
912			\|a GBV_ILN_2472
912			\|a GBV_ILN_2507
912			\|a GBV_ILN_2522
912			\|a GBV_ILN_2548
912			\|a GBV_ILN_4035
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4046
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4242
912			\|a GBV_ILN_4246
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4251
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
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912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4336
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4393
912			\|a GBV_ILN_4700
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allfields	10.1080/15598608.2014.910479 doi (DE-627)SPR038620316 (SPR)15598608.2014.910479-e DE-627 ger DE-627 rakwb eng Ahmad, Tanvir verfasserin aut Efficient Response Surface Designs for the Second-Order Multivariate Polynomial Model Robust to Missing Observation 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Grace Scientific Publishing 2015 Abstract Standard central composite design (CCD) originally requires that its factorial portion contains a full factorial design or fractional factorial design of resolution V or higher so that all effects of vital interest could be estimated. A CCD can be an ideal choice for lower number of factors (k). For k > 5, the standard CCD becomes very large and when, with the purpose of reduction of design size, the initial fractional factorial of resolution III or IV is used, the lower order effects are confounded. Block and Mee (2001) proposed some economical designs for k > 5. The designs were named as repaired resolution central composite (RRCC) designs; these actually repaired the portion containing factorial fractions of resolution III or IV. After repairing, the words of length four or lower were de-aliased and the effects of vital importance became estimable. In this study, some new versions of RRCC designs are constructed. All classes of designs are studied for their robustness to missing data. Loss of missing different kinds of design points has been computed. Central composite designs (dpeaa)DE-He213 Repaired resolution central composite designs (dpeaa)DE-He213 Missing observations (dpeaa)DE-He213 Minimax loss criterion (dpeaa)DE-He213 Akhtar, Munir aut Enthalten in Journal of statistical theory and practice Cham : Springer International Publishing, 2007 9(2015), 2 vom: 01. Juni, Seite 361-375 (DE-627)771398247 (DE-600)2740991-0 1559-8616 nnns volume:9 year:2015 number:2 day:01 month:06 pages:361-375 https://dx.doi.org/10.1080/15598608.2014.910479 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 9 2015 2 01 06 361-375
spelling	10.1080/15598608.2014.910479 doi (DE-627)SPR038620316 (SPR)15598608.2014.910479-e DE-627 ger DE-627 rakwb eng Ahmad, Tanvir verfasserin aut Efficient Response Surface Designs for the Second-Order Multivariate Polynomial Model Robust to Missing Observation 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Grace Scientific Publishing 2015 Abstract Standard central composite design (CCD) originally requires that its factorial portion contains a full factorial design or fractional factorial design of resolution V or higher so that all effects of vital interest could be estimated. A CCD can be an ideal choice for lower number of factors (k). For k > 5, the standard CCD becomes very large and when, with the purpose of reduction of design size, the initial fractional factorial of resolution III or IV is used, the lower order effects are confounded. Block and Mee (2001) proposed some economical designs for k > 5. The designs were named as repaired resolution central composite (RRCC) designs; these actually repaired the portion containing factorial fractions of resolution III or IV. After repairing, the words of length four or lower were de-aliased and the effects of vital importance became estimable. In this study, some new versions of RRCC designs are constructed. All classes of designs are studied for their robustness to missing data. Loss of missing different kinds of design points has been computed. Central composite designs (dpeaa)DE-He213 Repaired resolution central composite designs (dpeaa)DE-He213 Missing observations (dpeaa)DE-He213 Minimax loss criterion (dpeaa)DE-He213 Akhtar, Munir aut Enthalten in Journal of statistical theory and practice Cham : Springer International Publishing, 2007 9(2015), 2 vom: 01. Juni, Seite 361-375 (DE-627)771398247 (DE-600)2740991-0 1559-8616 nnns volume:9 year:2015 number:2 day:01 month:06 pages:361-375 https://dx.doi.org/10.1080/15598608.2014.910479 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 9 2015 2 01 06 361-375
allfields_unstemmed	10.1080/15598608.2014.910479 doi (DE-627)SPR038620316 (SPR)15598608.2014.910479-e DE-627 ger DE-627 rakwb eng Ahmad, Tanvir verfasserin aut Efficient Response Surface Designs for the Second-Order Multivariate Polynomial Model Robust to Missing Observation 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Grace Scientific Publishing 2015 Abstract Standard central composite design (CCD) originally requires that its factorial portion contains a full factorial design or fractional factorial design of resolution V or higher so that all effects of vital interest could be estimated. A CCD can be an ideal choice for lower number of factors (k). For k > 5, the standard CCD becomes very large and when, with the purpose of reduction of design size, the initial fractional factorial of resolution III or IV is used, the lower order effects are confounded. Block and Mee (2001) proposed some economical designs for k > 5. The designs were named as repaired resolution central composite (RRCC) designs; these actually repaired the portion containing factorial fractions of resolution III or IV. After repairing, the words of length four or lower were de-aliased and the effects of vital importance became estimable. In this study, some new versions of RRCC designs are constructed. All classes of designs are studied for their robustness to missing data. Loss of missing different kinds of design points has been computed. Central composite designs (dpeaa)DE-He213 Repaired resolution central composite designs (dpeaa)DE-He213 Missing observations (dpeaa)DE-He213 Minimax loss criterion (dpeaa)DE-He213 Akhtar, Munir aut Enthalten in Journal of statistical theory and practice Cham : Springer International Publishing, 2007 9(2015), 2 vom: 01. Juni, Seite 361-375 (DE-627)771398247 (DE-600)2740991-0 1559-8616 nnns volume:9 year:2015 number:2 day:01 month:06 pages:361-375 https://dx.doi.org/10.1080/15598608.2014.910479 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 9 2015 2 01 06 361-375
allfieldsGer	10.1080/15598608.2014.910479 doi (DE-627)SPR038620316 (SPR)15598608.2014.910479-e DE-627 ger DE-627 rakwb eng Ahmad, Tanvir verfasserin aut Efficient Response Surface Designs for the Second-Order Multivariate Polynomial Model Robust to Missing Observation 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Grace Scientific Publishing 2015 Abstract Standard central composite design (CCD) originally requires that its factorial portion contains a full factorial design or fractional factorial design of resolution V or higher so that all effects of vital interest could be estimated. A CCD can be an ideal choice for lower number of factors (k). For k > 5, the standard CCD becomes very large and when, with the purpose of reduction of design size, the initial fractional factorial of resolution III or IV is used, the lower order effects are confounded. Block and Mee (2001) proposed some economical designs for k > 5. The designs were named as repaired resolution central composite (RRCC) designs; these actually repaired the portion containing factorial fractions of resolution III or IV. After repairing, the words of length four or lower were de-aliased and the effects of vital importance became estimable. In this study, some new versions of RRCC designs are constructed. All classes of designs are studied for their robustness to missing data. Loss of missing different kinds of design points has been computed. Central composite designs (dpeaa)DE-He213 Repaired resolution central composite designs (dpeaa)DE-He213 Missing observations (dpeaa)DE-He213 Minimax loss criterion (dpeaa)DE-He213 Akhtar, Munir aut Enthalten in Journal of statistical theory and practice Cham : Springer International Publishing, 2007 9(2015), 2 vom: 01. Juni, Seite 361-375 (DE-627)771398247 (DE-600)2740991-0 1559-8616 nnns volume:9 year:2015 number:2 day:01 month:06 pages:361-375 https://dx.doi.org/10.1080/15598608.2014.910479 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 9 2015 2 01 06 361-375
allfieldsSound	10.1080/15598608.2014.910479 doi (DE-627)SPR038620316 (SPR)15598608.2014.910479-e DE-627 ger DE-627 rakwb eng Ahmad, Tanvir verfasserin aut Efficient Response Surface Designs for the Second-Order Multivariate Polynomial Model Robust to Missing Observation 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Grace Scientific Publishing 2015 Abstract Standard central composite design (CCD) originally requires that its factorial portion contains a full factorial design or fractional factorial design of resolution V or higher so that all effects of vital interest could be estimated. A CCD can be an ideal choice for lower number of factors (k). For k > 5, the standard CCD becomes very large and when, with the purpose of reduction of design size, the initial fractional factorial of resolution III or IV is used, the lower order effects are confounded. Block and Mee (2001) proposed some economical designs for k > 5. The designs were named as repaired resolution central composite (RRCC) designs; these actually repaired the portion containing factorial fractions of resolution III or IV. After repairing, the words of length four or lower were de-aliased and the effects of vital importance became estimable. In this study, some new versions of RRCC designs are constructed. All classes of designs are studied for their robustness to missing data. Loss of missing different kinds of design points has been computed. Central composite designs (dpeaa)DE-He213 Repaired resolution central composite designs (dpeaa)DE-He213 Missing observations (dpeaa)DE-He213 Minimax loss criterion (dpeaa)DE-He213 Akhtar, Munir aut Enthalten in Journal of statistical theory and practice Cham : Springer International Publishing, 2007 9(2015), 2 vom: 01. Juni, Seite 361-375 (DE-627)771398247 (DE-600)2740991-0 1559-8616 nnns volume:9 year:2015 number:2 day:01 month:06 pages:361-375 https://dx.doi.org/10.1080/15598608.2014.910479 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 9 2015 2 01 06 361-375
language	English
source	Enthalten in Journal of statistical theory and practice 9(2015), 2 vom: 01. Juni, Seite 361-375 volume:9 year:2015 number:2 day:01 month:06 pages:361-375
sourceStr	Enthalten in Journal of statistical theory and practice 9(2015), 2 vom: 01. Juni, Seite 361-375 volume:9 year:2015 number:2 day:01 month:06 pages:361-375
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Central composite designs Repaired resolution central composite designs Missing observations Minimax loss criterion
isfreeaccess_bool	false
container_title	Journal of statistical theory and practice
authorswithroles_txt_mv	Ahmad, Tanvir @@aut@@ Akhtar, Munir @@aut@@
publishDateDaySort_date	2015-06-01T00:00:00Z
hierarchy_top_id	771398247
id	SPR038620316
language_de	englisch
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author	Ahmad, Tanvir
spellingShingle	Ahmad, Tanvir misc Central composite designs misc Repaired resolution central composite designs misc Missing observations misc Minimax loss criterion Efficient Response Surface Designs for the Second-Order Multivariate Polynomial Model Robust to Missing Observation
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topic_title	Efficient Response Surface Designs for the Second-Order Multivariate Polynomial Model Robust to Missing Observation Central composite designs (dpeaa)DE-He213 Repaired resolution central composite designs (dpeaa)DE-He213 Missing observations (dpeaa)DE-He213 Minimax loss criterion (dpeaa)DE-He213
topic	misc Central composite designs misc Repaired resolution central composite designs misc Missing observations misc Minimax loss criterion
topic_unstemmed	misc Central composite designs misc Repaired resolution central composite designs misc Missing observations misc Minimax loss criterion
topic_browse	misc Central composite designs misc Repaired resolution central composite designs misc Missing observations misc Minimax loss criterion
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title	Efficient Response Surface Designs for the Second-Order Multivariate Polynomial Model Robust to Missing Observation
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title_full	Efficient Response Surface Designs for the Second-Order Multivariate Polynomial Model Robust to Missing Observation
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author_browse	Ahmad, Tanvir Akhtar, Munir
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author-letter	Ahmad, Tanvir
doi_str_mv	10.1080/15598608.2014.910479
title_sort	efficient response surface designs for the second-order multivariate polynomial model robust to missing observation
title_auth	Efficient Response Surface Designs for the Second-Order Multivariate Polynomial Model Robust to Missing Observation
abstract	Abstract Standard central composite design (CCD) originally requires that its factorial portion contains a full factorial design or fractional factorial design of resolution V or higher so that all effects of vital interest could be estimated. A CCD can be an ideal choice for lower number of factors (k). For k > 5, the standard CCD becomes very large and when, with the purpose of reduction of design size, the initial fractional factorial of resolution III or IV is used, the lower order effects are confounded. Block and Mee (2001) proposed some economical designs for k > 5. The designs were named as repaired resolution central composite (RRCC) designs; these actually repaired the portion containing factorial fractions of resolution III or IV. After repairing, the words of length four or lower were de-aliased and the effects of vital importance became estimable. In this study, some new versions of RRCC designs are constructed. All classes of designs are studied for their robustness to missing data. Loss of missing different kinds of design points has been computed. © Grace Scientific Publishing 2015
abstractGer	Abstract Standard central composite design (CCD) originally requires that its factorial portion contains a full factorial design or fractional factorial design of resolution V or higher so that all effects of vital interest could be estimated. A CCD can be an ideal choice for lower number of factors (k). For k > 5, the standard CCD becomes very large and when, with the purpose of reduction of design size, the initial fractional factorial of resolution III or IV is used, the lower order effects are confounded. Block and Mee (2001) proposed some economical designs for k > 5. The designs were named as repaired resolution central composite (RRCC) designs; these actually repaired the portion containing factorial fractions of resolution III or IV. After repairing, the words of length four or lower were de-aliased and the effects of vital importance became estimable. In this study, some new versions of RRCC designs are constructed. All classes of designs are studied for their robustness to missing data. Loss of missing different kinds of design points has been computed. © Grace Scientific Publishing 2015
abstract_unstemmed	Abstract Standard central composite design (CCD) originally requires that its factorial portion contains a full factorial design or fractional factorial design of resolution V or higher so that all effects of vital interest could be estimated. A CCD can be an ideal choice for lower number of factors (k). For k > 5, the standard CCD becomes very large and when, with the purpose of reduction of design size, the initial fractional factorial of resolution III or IV is used, the lower order effects are confounded. Block and Mee (2001) proposed some economical designs for k > 5. The designs were named as repaired resolution central composite (RRCC) designs; these actually repaired the portion containing factorial fractions of resolution III or IV. After repairing, the words of length four or lower were de-aliased and the effects of vital importance became estimable. In this study, some new versions of RRCC designs are constructed. All classes of designs are studied for their robustness to missing data. Loss of missing different kinds of design points has been computed. © Grace Scientific Publishing 2015
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title_short	Efficient Response Surface Designs for the Second-Order Multivariate Polynomial Model Robust to Missing Observation
url	https://dx.doi.org/10.1080/15598608.2014.910479
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up_date	2024-07-03T19:09:52.926Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR038620316</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230328215354.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201007s2015 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1080/15598608.2014.910479</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR038620316</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)15598608.2014.910479-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Ahmad, Tanvir</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Efficient Response Surface Designs for the Second-Order Multivariate Polynomial Model Robust to Missing Observation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Grace Scientific Publishing 2015</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Standard central composite design (CCD) originally requires that its factorial portion contains a full factorial design or fractional factorial design of resolution V or higher so that all effects of vital interest could be estimated. A CCD can be an ideal choice for lower number of factors (k). For k > 5, the standard CCD becomes very large and when, with the purpose of reduction of design size, the initial fractional factorial of resolution III or IV is used, the lower order effects are confounded. Block and Mee (2001) proposed some economical designs for k > 5. The designs were named as repaired resolution central composite (RRCC) designs; these actually repaired the portion containing factorial fractions of resolution III or IV. After repairing, the words of length four or lower were de-aliased and the effects of vital importance became estimable. In this study, some new versions of RRCC designs are constructed. All classes of designs are studied for their robustness to missing data. 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Juni, Seite 361-375</subfield><subfield code="w">(DE-627)771398247</subfield><subfield code="w">(DE-600)2740991-0</subfield><subfield code="x">1559-8616</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:9</subfield><subfield code="g">year:2015</subfield><subfield code="g">number:2</subfield><subfield code="g">day:01</subfield><subfield code="g">month:06</subfield><subfield code="g">pages:361-375</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1080/15598608.2014.910479</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" 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Efficient Response Surface Designs for the Second-Order Multivariate Polynomial Model Robust to Missing Observation

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