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Assessing local influence in linear regression models with first-order autoregressive or heteroscedastic error structure

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  • Tsai, Chih-Ling
  • Wu, Xizhi

Abstract

The local influence approach to the linear regression model with first-order autoregressive errors is developed and discussed. An advantage of this approach is that it avoids the inappropriate case-deletion diagnostic in the autoregressive model and it also allows simultaneous perturbations on all responses. Analogously, we obtain the local influence diagnostic on the weighted regression parameter estimate when the heteroscedastic error structure is considered.

Suggested Citation

  • Tsai, Chih-Ling & Wu, Xizhi, 1992. "Assessing local influence in linear regression models with first-order autoregressive or heteroscedastic error structure," Statistics & Probability Letters, Elsevier, vol. 14(3), pages 247-252, June.
  • Handle: RePEc:eee:stapro:v:14:y:1992:i:3:p:247-252
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    Citations

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    Cited by:

    1. Ortega, Edwin M. M. & Bolfarine, Heleno & Paula, Gilberto A., 2003. "Influence diagnostics in generalized log-gamma regression models," Computational Statistics & Data Analysis, Elsevier, vol. 42(1-2), pages 165-186, February.
    2. Paula, Gilberto A. & Medeiros, Marcio & Vilca-Labra, Filidor E., 2009. "Influence diagnostics for linear models with first-order autoregressive elliptical errors," Statistics & Probability Letters, Elsevier, vol. 79(3), pages 339-346, February.
    3. Víctor Lachos & Filidor Vilca & Manuel Galea, 2007. "Influence diagnostics for the Grubbs's model," Statistical Papers, Springer, vol. 48(3), pages 419-436, September.
    4. Yonghui Liu & Ruochen Sang & Shuangzhe Liu, 2017. "Diagnostic analysis for a vector autoregressive model under Student-super-′s t-distributions," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 71(2), pages 86-114, May.
    5. Cadigan, N. G. & Farrell, P. J., 1999. "Expected local influence in the normal linear regression model," Statistics & Probability Letters, Elsevier, vol. 41(1), pages 25-30, January.
    6. Shi, Lei & Wang, Xueren, 1999. "Local influence in ridge regression," Computational Statistics & Data Analysis, Elsevier, vol. 31(3), pages 341-353, September.
    7. Rasekh, A.R., 2006. "Local influence in measurement error models with ridge estimate," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2822-2834, June.

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