Bootstrapping M-estimates in regression and autoregression with infinite variance

Statistica Sinica

Volumn 7, Issue 4, 1997, Pages 1135-1154

  Davis, Richard A ^a   Wu, Wei ^a,b  

^a Veterinary Dentistry and Oral Surgery   (United States)

^b MERCK RESEARCH LABORATORIES   (United States)

Author keywords

Autoregressive processes; Bootstrap; M estimation; Poisson processes; Regular variation; Stable laws

Indexed keywords

EID: 0031314428     PISSN: 10170405     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (8)

1. Athreya, K. B. (1987). Bootstrap of the mean in the infinite variance case. Ann. Statist. 15, 724-731.
2. Athreya, K. B., Lahiri, S. and Wu, W. (1993). Inference for heavy tailed distributions. Preprint.
3. Billingsley, P. (1968). Weak Convergence of Probability Measures. Wiley, New York.
4. Davis, R. A., Knight, K. and Liu, J. (1992). M-estimation for autoregressions with infinite variance. Stochastic Proc. Appl. 40, 145-180.
5. Davis, R. A. and Resnick, S. I. (1985). Limit theory for moving averages of random variables with regularly varying tail probabilities. Ann. Probab. 13, 179-195.
6. Davis, R. A. and Wu, W. (1997). M-estimation for linear regression and autoregression with infinite variance. Probab. Math. Statist. 17, 117-136.
7. Leadbetter, M. R., Lindgren, G. and Rootzén, H. (1983). Extremes and Related Properties of Random Sequences and Processes. Springer-Verlag, New York.
8. Resnick, S. I. (1987). Extreme Values, Regular Variation, and Point Processes. Springer-Verlag, New York.