theorem A.214 Wilks, $k$ parameters and $r$ constraints

open in the book · appendices/A-long-proofs.tex:10904 · p. 2896

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theorem A.214: Wilks, k parameters and r constraintsA.214lemma A.213: The three minimaA.213lemma 11.83: Gaussian quadratic forms11.83theorem A.206: Cramér–Wold, and continuous mappingA.206proof : app:A-long-proofs@proof-132proofcorollary A.210: Uniform quadratic approximation on the n^-1/2 scaleA.210lemma A.212: Second-order flatnessA.212lemma A.211: Root-n localisationA.211proof : app:A-long-proofs@proof-131proofdefinition 11.80: Chi-squared11.80corollary 11.84: Residuals about a weighted mean; the Birge ratio11.84example 33.15: The six values are mutually inconsistent, and by how much33.15theorem 11.88: Wilks11.88proof : ch:09-probability-statistics@proof-36proofdefinition 11.21: Distribution function11.21lemma 11.52: Slutsky11.52lemma A.208: The three averagesA.208

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typedirectionnode provenancewhere
depends_on The three minima declared appendices/A-long-proofs.tex:10914
depends_on Gaussian quadratic forms declared appendices/A-long-proofs.tex:10914
depends_on Cramér–Wold, and continuous mapping declared appendices/A-long-proofs.tex:10914
proves app:A-long-proofs@proof-132 declared appendices/A-long-proofs.tex:10918