Functional central limit theorems for self-normalized least squares processes in regression with possibly infinite variance data (Q645604)
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scientific article; zbMATH DE number 5969765
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Functional central limit theorems for self-normalized least squares processes in regression with possibly infinite variance data |
scientific article; zbMATH DE number 5969765 |
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Functional central limit theorems for self-normalized least squares processes in regression with possibly infinite variance data (English)
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10 November 2011
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simple linear regression
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domain of attraction of the normal law
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infinite variance
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slowly varying function at infinity
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studentized/self-normalized least squares estimator/process
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Cholesky square root of a matrix
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symmetric positive definite square root of a matrix
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standard/bivariate Wiener process
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functional central limit theorem
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sup
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norm approximation in probability
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direct product of two measurable spaces
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uniform Euclidean norm approximation in probability
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asymptotic confidence interval
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signal-to-noise ratio
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generalized domain of attraction of the \(d\)-variate normal law
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0.91530913
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0.91158015
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0.9032605
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0.89952564
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0.8854131
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0.88023406
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