Theoretical Statistics¶
Cox, D. R., & Hinkley, D. V. (1974). Theoretical Statistics. Chapman and Hall.
Cited by¶
3 citations across 3 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Aggregation
- Distinguishing aggregation from neighboring operations such as compression, simple averaging, sampling, and binning matters because each makes a different commitment about what is preserved and what is destroyed, as Cox and Hinkley (1974) develop in their canonical treatment of statistical inference and data reduction.
This sourceCanonical treatment of statistical inference, sufficiency, and data reduction; supports distinguishing aggregation from neighboring data-reduction operations (what is preserved vs destroyed).
- Distinguishing aggregation from neighboring operations such as compression, simple averaging, sampling, and binning matters because each makes a different commitment about what is preserved and what is destroyed, as Cox and Hinkley (1974) develop in their canonical treatment of statistical inference and data reduction.
- Distributional Assumption
- A time-series model might assume stationarity (a temporal assumption) and normal errors (a distributional assumption); these are distinct commitments, a separation Cox and Hinkley (1974) draw carefully in their theoretical statistics framework.
This sourceClassic text on statistical theory: separates distributional assumptions (shape of error/data distribution) from structural assumptions (functional form, independence, stationarity) as orthogonal modeling commitments.
- A time-series model might assume stationarity (a temporal assumption) and normal errors (a distributional assumption); these are distinct commitments, a separation Cox and Hinkley (1974) draw carefully in their theoretical statistics framework.
Domain-specific¶
Verification¶
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Links previously used in the corpus¶
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Registry ID ref:f8bda05ef5c9 · see in the full table