Journal of Information and Knowledge (Formerly SRELS Journal of Information Management)

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A Statistical Search Method for Estimation of Bradford Groups


Affiliations
1 Economic Analysis Unit, Indian Statistical Institute, Mysore Road, RVCE Post, Bangalore-560 059, India
2 S. V. University Library, Sri Venkateswara University, Tirupati-517 502, India
     

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Bradford's Law in bibliometrics is viewed as consisting of two aspects. First one is the distribution aspect which is purely a mathematical pattern. The other aspect is the relevance of such a distribution to bibliometrics. This paper deals with the methodology for estimating Bradford groups within a given set of bibliometric data. The paper also proposes a simple and easily adaptable statistical search method (SSM) and illustrates the application of the method.

Keywords

Bradford Distribution/Groups/Law, Geometric Progression, Degree of Concentration, Chi-Square Test, Root Mean Square Error.
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About The Authors

N. S. S. Narayana
Economic Analysis Unit, Indian Statistical Institute, Mysore Road, RVCE Post, Bangalore-560 059
India

C. Aruna Prasad Reddy
S. V. University Library, Sri Venkateswara University, Tirupati-517 502
India


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  • A Statistical Search Method for Estimation of Bradford Groups

Abstract Views: 504  |  PDF Views: 12

Authors

N. S. S. Narayana
Economic Analysis Unit, Indian Statistical Institute, Mysore Road, RVCE Post, Bangalore-560 059, India
C. Aruna Prasad Reddy
S. V. University Library, Sri Venkateswara University, Tirupati-517 502, India

Abstract


Bradford's Law in bibliometrics is viewed as consisting of two aspects. First one is the distribution aspect which is purely a mathematical pattern. The other aspect is the relevance of such a distribution to bibliometrics. This paper deals with the methodology for estimating Bradford groups within a given set of bibliometric data. The paper also proposes a simple and easily adaptable statistical search method (SSM) and illustrates the application of the method.

Keywords


Bradford Distribution/Groups/Law, Geometric Progression, Degree of Concentration, Chi-Square Test, Root Mean Square Error.