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Information Journal Paper

Title

INFLUENCE FUNCTIONS IN FUNCTIONAL MEASUREMENT ERROR MODELS WITH RIDGE ESTIMATION

Pages

  65-78

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Abstract

 Ridge estimator has been suggested as an alternative to the maximum likelihood estimator in the presence of collinearity among the elements of unobservable values in functional measurement error models. We derive the influence function of the individual observations on the ridge estimate in this context. We also derive different versions of the sample influence functions and we define the Cook's statistic analogues to one given in ordinary linear regression models. Finally, using the influence function we will find the asymptotic distribution of the ridge estimator. Among different results, we show that influence of each observation on the ridge estimator is linear combination of influence on the maximum likelihood estimator.

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    APA: Copy

    RASEKH, A.A.R., & BAGHERI, A.. (2002). INFLUENCE FUNCTIONS IN FUNCTIONAL MEASUREMENT ERROR MODELS WITH RIDGE ESTIMATION . RESEARCH JOURNAL OF UNIVERSITY OF ISFAHAN "SCIENCE", 16(1-2), 65-78. SID. https://sid.ir/paper/55868/en

    Vancouver: Copy

    RASEKH A.A.R., BAGHERI A.. INFLUENCE FUNCTIONS IN FUNCTIONAL MEASUREMENT ERROR MODELS WITH RIDGE ESTIMATION . RESEARCH JOURNAL OF UNIVERSITY OF ISFAHAN "SCIENCE"[Internet]. 2002;16(1-2):65-78. Available from: https://sid.ir/paper/55868/en

    IEEE: Copy

    A.A.R. RASEKH, and A. BAGHERI, “INFLUENCE FUNCTIONS IN FUNCTIONAL MEASUREMENT ERROR MODELS WITH RIDGE ESTIMATION ,” RESEARCH JOURNAL OF UNIVERSITY OF ISFAHAN "SCIENCE", vol. 16, no. 1-2, pp. 65–78, 2002, [Online]. Available: https://sid.ir/paper/55868/en

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