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A boundary null has a nonstandard likelihood-ratio limit
Statement refuted
For the one-sided null in a smooth normal location model, the likelihood-ratio statistic has a limit at merely because is interior to the full parameter space.
Facts & Assumptions
Given: AC, a known , and iid observations from with null set and true value .
Wald, score, and likelihood-ratio statistics for regular nulls: the likelihood-ratio statistic is twice the unrestricted-minus-restricted maximized log likelihood.
Quadratic-mean differentiability at a parameter: in one dimension, QMD with score requires and .
Standard normal and normal laws: has the even density , and is its affine image.
Characteristic function of a normal law: a variable has characteristic function , mean , and variance .
Characteristic functions under affine maps and independent sums: affine maps and finite independent sums transform characteristic functions by the affine rule and product rule.
Uniqueness of a law from its characteristic function: under AC, equal characteristic functions determine equal Borel probability laws.
Chi-square laws, including zero degrees: is the law of the square of one standard-normal coordinate.
Cauchy-Schwarz inequality for : for square-integrable functions, the integral of the absolute product is at most the product of their norms.
Tonelli's theorem for nonnegative measurable functions on a sigma-finite product: a nonnegative product-measurable function on sigma-finite spaces can be integrated by either iterated integral.
The second fundamental theorem: if is differentiable on with and is integrable, then : if on a compact interval and is integrable, then .
The Axiom of Choice: AC is used by the normal characteristic-function, uniqueness, and chi-square-law suppliers [F4], [F6], and [F7].
Gaussian even moments for Brownian increments: under AC, a centered normal variable of variance has second and fourth moments and . To instantiate the supplier, take the centered normal variable as , the constant as , and the labels , , then use ; no Brownian process is needed.
Integrating against a density agrees with integrating the product: integration against a density is integration of the product.
A continuous function on is Riemann integrable, by Heine-Cantor and Riemann's criterion: continuous functions on compact parameter intervals are bounded and Riemann integrable.
A bounded Riemann integrable function on a closed bounded interval is Lebesgue measurable and has the same integral: under Countable Choice, bounded Riemann-integrable functions have the same Lebesgue integral on a compact interval; the assumed AC supplies this premise.
Lebesgue outer measure, Lebesgue measurability and Lebesgue measure are unchanged by translation: translation preserves Lebesgue measurability and measure. For a nonnegative measurable function, translating each simple function below it gives a bijection of the simple minorants with unchanged integrals; taking the defining supremum therefore preserves its nonnegative integral.
Counterexample
Take the full parameter space and the null . The true point is interior to but is the boundary point of .
Given: The model, null, and true value above.
Put . Direct differentiation gives and . Its square is a polynomial times . By [F11] and [F12], and , so . Also has second moment . The identity and [F15] give the same norm for every real shift . The two-variable functions and are continuous. To verify the needed product measurability locally, the rectangles with rational endpoints form a countable base of : inside any open ball about a point, density of the rationals gives a rational rectangle containing that point and contained in the ball. Every open subset is therefore the union of the subfamily of these rectangles contained in it, hence a countable union of measurable product rectangles. Thus preimages of open subsets under these continuous functions belong to , and also to the product of the Lebesgue sigma-algebras. Their squares and restrictions to compact parameter intervals are consequently product measurable, as required by Tonelli below.
The log likelihood is a constant minus . Completing the square shows that the unrestricted MLE is and the constrained MLE is : when the unrestricted maximum is feasible, and when the closest feasible point is .
For fixed , the functions and are continuous on each compact interval. By [F13] they are Riemann integrable, by [F10] their integrals are respectively and , and [F14] identifies these with their Lebesgue integrals under the assumed AC. Reversed endpoints give the same identities for negative .
Substituting these maximizers into [F1] gives This follows from : the difference is zero for , and otherwise it is after multiplication by .
Cauchy–Schwarz [F8] on the interval between and , then Tonelli [F9] and step 1.1, gives . The second identity of step 2.1 and another Cauchy–Schwarz/Tonelli application give . For negative use on the length- interval; the same first bound holds. This proves QMD with the explicitly supplied normal densities, score , and positive information by [F2].
Under , put . By [F4] and [F5], ; uniqueness [F6] gives exactly. Its even density [F3] gives , and for the distribution function of is , where . Thus its law is , by [F7]. Since [F3] gives , has no atom at zero, so this mixture is not the ordinary law. The failure comes from the null's half-line local tangent, not a boundary of the full parameter space.
Depends on
- Wald, score, and likelihood-ratio statistics for regular nulls
- Quadratic-mean differentiability at a parameter
- Standard normal and normal laws
- Characteristic function of a normal law
- Characteristic functions under affine maps and independent sums
- Uniqueness of a law from its characteristic function
- Chi-square laws, including zero degrees
- Cauchy-Schwarz inequality for $L^2$
- Tonelli's theorem for nonnegative measurable functions on a sigma-finite product
- The second fundamental theorem: if $G$ is differentiable on $[a,b]$ with $G' = f$ and $f$ is integrable, then $\int_a^b f = G(b)-G(a)$
- The Axiom of Choice
- Gaussian even moments for Brownian increments
- Integrating against a density agrees with integrating the product
- A continuous function on $[a,b]$ is Riemann integrable, by Heine-Cantor and Riemann's criterion
- A bounded Riemann integrable function on a closed bounded interval is Lebesgue measurable and has the same integral
- Lebesgue outer measure, Lebesgue measurability and Lebesgue measure are unchanged by translation
Used by
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Sources
- Peter Bartlett, Theoretical Statistics, Stat 210B Lecture 26, PDF pp. 18–20 (standard reference, not scraped)
- Yen-Chi Chen, STAT 581 Chapter 4: Hypothesis tests in likelihood models, geometry discussion (standard reference, not scraped)