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Information Journal Paper

Title

USING KULLBACK-LEIBLER DISTANCE FOR PERFORMANCE EVALUATION OF SEARCH DESIGNS

Pages

  269-279

Abstract

 This paper considers the search problem, introduced by Srivastava [10]. This is a model discrimination problem. In the context of SEARCH LINEAR MODELs, discrimination ability of search de-signs has been studied by several researchers. Some criteria have been developed to measure this capability, however, they are re-stricted in a sense of being able to work for searching only one possible nonzero effect. In this paper, two criteria are proposed, based on KULLBACK-LEIBLER DISTANCE. These criteria are able to eval-uate the search ability of designs, without any restriction on the number of nonzero effects.

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    • Cite

    APA: Copy

    TALEBI, H., & ESMAILZADEH, N.. (2011). USING KULLBACK-LEIBLER DISTANCE FOR PERFORMANCE EVALUATION OF SEARCH DESIGNS. BULLETIN OF THE IRANIAN MATHEMATICAL SOCIETY, 37(4), 269-279. SID. https://sid.ir/paper/642346/en

    Vancouver: Copy

    TALEBI H., ESMAILZADEH N.. USING KULLBACK-LEIBLER DISTANCE FOR PERFORMANCE EVALUATION OF SEARCH DESIGNS. BULLETIN OF THE IRANIAN MATHEMATICAL SOCIETY[Internet]. 2011;37(4):269-279. Available from: https://sid.ir/paper/642346/en

    IEEE: Copy

    H. TALEBI, and N. ESMAILZADEH, “USING KULLBACK-LEIBLER DISTANCE FOR PERFORMANCE EVALUATION OF SEARCH DESIGNS,” BULLETIN OF THE IRANIAN MATHEMATICAL SOCIETY, vol. 37, no. 4, pp. 269–279, 2011, [Online]. Available: https://sid.ir/paper/642346/en

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