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Estimating linear relationships for models based on random variables with infinite variance
Technical documentation   Open access

Estimating linear relationships for models based on random variables with infinite variance

Marek Kanter and William L. Steiger
Rutgers University
1974
DOI:
https://doi.org/10.7282/t3-0wnf-kv79

Abstract

Stable Process Autoregressive Process Moving Average Process Regression
We sketch the proof of some theorems that show how to estimate the parameters in linear regressions, finite moving averages, and in finite order, stationary auto regressions. Some of these estimates have not been studied yet, but the chief novelty is that existing theory is extended to include processes with infinite variance. A main result is that ordinary least squares estimates are consistent for both finite moving average processes and finite order auto regressions. The sampling properties of some of these estimates are indicated.
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