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Some New Methods for Local Sensitivity Analysis in Statistics

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Advances in Distribution Theory, Order Statistics, and Inference

Part of the book series: Statistics for Industry and Technology ((SIT))

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Abstract

This chapter deals with the problem of local sensitivity analysis, that is, how sensitive the results of a statistical analysis are to a change in the data. A closed formula for the calculation of local sensitivities in optimization problems is applied to some optimization problems in statistics, including regression, maximum likelihood, and other situations involving ordered and data constrained parameters. In addition, a general method for evaluating the sensitivities for the method of moments is obtained. The methods are illustrated with several examples.

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Author information

Authors and Affiliations

  1. University of Cantabria, Santander, Spain

    Enrique Castillo & J. M. Sarabia

  2. University of Granada, Santander, Spain

    Carmen Castillo

  3. The American University in Cairo, Cairo, Egypt

    Ali S. Hadi

Authors
  1. Enrique Castillo
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  2. Carmen Castillo
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  3. Ali S. Hadi
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  4. J. M. Sarabia
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Statistics, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S 4K1, Canada

    N. Balakrishnan

  2. Department of Economics, University of Cantabria, s/n Avenida de los Castros, Santander, 39005, Spain

    José María Sarabia  & Enrique Castillo  & 

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© 2006 Birkhäuser Boston

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Castillo, E., Castillo, C., Hadi, A.S., Sarabia, J.M. (2006). Some New Methods for Local Sensitivity Analysis in Statistics. In: Balakrishnan, N., Sarabia, J.M., Castillo, E. (eds) Advances in Distribution Theory, Order Statistics, and Inference. Statistics for Industry and Technology. Birkhäuser Boston. https://doi.org/10.1007/0-8176-4487-3_22

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