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A boundary null has a nonstandard likelihood-ratio limit

Statement refuted

For the one-sided null H0:μ≤0 in a smooth normal location model, the likelihood-ratio statistic has a χ12 limit at μ=0 merely because μ=0 is interior to the full parameter space.

Facts & Assumptions

Given: AC, a known σ>0, and iid observations from N(μ,σ2) with null set Θ0=(−∞,0] and true value μ=0.

[F1]

Wald, score, and likelihood-ratio statistics for regular nulls: the likelihood-ratio statistic is twice the unrestricted-minus-restricted maximized log likelihood.

[F2]

Quadratic-mean differentiability at a parameter: in one dimension, QMD with score sμ requires ∥pμ+t−pμ−12tsμpμ∥2=o(∣t∣) and sμ∈L2(Pμ).

[F3]

Standard normal and normal laws: N(0,1) has the even density e−x2/2/2π, and N(μ,σ2) is its affine image.

[F4]

Characteristic function of a normal law: a N(m,τ2) variable has characteristic function exp⁡(imt−τ2t2/2), mean m, and variance τ2.

[F5]

Characteristic functions under affine maps and independent sums: affine maps and finite independent sums transform characteristic functions by the affine rule and product rule.

[F6]

Uniqueness of a law from its characteristic function: under AC, equal characteristic functions determine equal Borel probability laws.

[F7]

Chi-square laws, including zero degrees: χ12 is the law of the square of one standard-normal coordinate.

[F8]

Cauchy-Schwarz inequality for L2: for square-integrable functions, the integral of the absolute product is at most the product of their L2 norms.

[F9]

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.

[F10]
[A1]

The Axiom of Choice: AC is used by the normal characteristic-function, uniqueness, and chi-square-law suppliers [F4], [F6], and [F7].

[F11]

Gaussian even moments for Brownian increments: under AC, a centered normal variable of variance σ2 has second and fourth moments σ2 and 3σ4. To instantiate the supplier, take the centered normal variable Y as Xt, the constant 0 as Xs, and the labels s=0, t=σ2, then use m=1,2; no Brownian process is needed.

[F12]

Integrating against a density agrees with integrating the product: integration against a density is integration of the product.

[F13]

A continuous function on [a,b] is Riemann integrable, by Heine-Cantor and Riemann's criterion: continuous functions on compact parameter intervals are bounded and Riemann integrable.

[F14]

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.

[F15]

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 Θ=R and the null Θ0=(−∞,0]. The true point μ=0 is interior to Θ but is the boundary point of Θ0.

Given: The model, null, and true value above.

1.1F11F12F15givenalgebra

Put qμ(x)=(2πσ2)−1/4e−(x−μ)2/(4σ2). Direct differentiation gives qμ′=(x−μ)qμ/(2σ2) and qμ′′=((x−μ)2/(4σ4)−1/(2σ2))qμ. Its square is a polynomial times pμ=qμ2. By [F11] and [F12], ∫(x−μ)2pμ dx=σ2 and ∫(x−μ)4pμ dx=3σ4, so ∥qμ′′∥22=3/(16σ4)<∞. Also sμ=2qμ′/qμ=(x−μ)/σ2 has second moment 1/σ2. The identity qa′′(x)=q0′′(x−a) and [F15] give the same norm for every real shift a. The two-variable functions (x,v)↦qμ+v′′(x) and (x,u)↦qμ+u′(x)−qμ′(x) are continuous. To verify the needed product measurability locally, the rectangles (a,b)×(c,d) with rational endpoints form a countable base of R2: 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 B(R)⊗B(R), 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.

1.2givenalgebra

The log likelihood is a constant minus (2σ2)−1∑i(Xi−μ)2. Completing the square shows that the unrestricted MLE is μ^=Xˉ and the constrained MLE is μ~=min⁡(0,Xˉ): when Xˉ≤0 the unrestricted maximum is feasible, and when Xˉ>0 the closest feasible point is 0.

2.1F13F10F14step 1.1given

For fixed x, the functions v↦qμ+v′′(x) and u↦qμ+u′(x)−qμ′(x) are continuous on each compact interval. By [F13] they are Riemann integrable, by [F10] their integrals are respectively qμ+u′(x)−qμ′(x) and qμ+t(x)−qμ(x)−tqμ′(x), and [F14] identifies these with their Lebesgue integrals under the assumed AC. Reversed endpoints give the same identities for negative u,t.

2.2F1step 1.2algebra

Substituting these maximizers into [F1] gives Ln=2{ℓn(μ^)−ℓn(μ~)}=n(Xˉ+)2σ2,Xˉ+=max⁡(Xˉ,0). This follows from ∑i(Xi−μ)2=∑i(Xi−Xˉ)2+n(μ−Xˉ)2: the difference is zero for Xˉ≤0, and otherwise it is nXˉ2/σ2 after multiplication by 2.

3.1F8F9F2step 1.1step 2.1algebra

Cauchy–Schwarz [F8] on the interval between 0 and u, then Tonelli [F9] and step 1.1, gives ∥qμ+u′−qμ′∥22≤u2∥q0′′∥22. The second identity of step 2.1 and another Cauchy–Schwarz/Tonelli application give ∥qμ+t−qμ−tqμ′∥22≤∣t∣∫0∣t∣u2∥q0′′∥22du=∣t∣4∥q0′′∥22/3=o(t2). For negative t use qμ−u′ on the length-∣t∣ interval; the same first bound holds. This proves QMD with the explicitly supplied normal densities, score sμ, and positive information 1/σ2 by [F2].

4.1A1F3F4F5F6F7step 2.2algebra∎

Under μ=0, put Z=nXˉ/σ. By [F4] and [F5], EeitZ=∏i=1ne−t2/(2n)=e−t2/2; uniqueness [F6] gives Z∼N(0,1) exactly. Its even density [F3] gives P(Z≤0)=1/2, and for t≥0 the distribution function of Ln=(Z+)2 is P(Z≤t)=Φ(t), where Φ(x):=P(Z≤x). Thus its law is 12δ0+12χ12, by [F7]. Since [F3] gives P(Z=0)=0, χ12 has no atom at zero, so this mixture is not the ordinary χ12 law. The failure comes from the null's half-line local tangent, not a boundary of the full parameter space.

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