Summary
This paper proves an asymptotic uniform quadraticity of certain statistics based on randomly weighted residual empirical processes under fairly general conditions. This result is useful in many statistical inference problems pertaining to linear models including the Correlation and Autoregression models. Some applications to the goodness of fit tests and minimum distance estimation in linear models are given.
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Koul, H.L. A quadraticity limit theorem useful in linear models. Probab. Th. Rel. Fields 82, 371–386 (1989). https://doi.org/10.1007/BF00339993
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DOI: https://doi.org/10.1007/BF00339993
Keywords
- Linear Model
- Stochastic Process
- General Condition
- Probability Theory
- Limit Theorem