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TheoremStatement: AI-adaptedProof: AI-adaptedPipeline-generatedjudge pass (gpt-6-luna)
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The discrete L-curve rule terminates with failure or a maximum-curvature grid point

Statement

For every admissible finite input to Discrete maximum-curvature L-curve parameter selection, the algorithm terminates. It returns failure exactly when fewer than three positive-residual, positive-solution-norm grid points remain. Otherwise it returns a retained grid parameter whose assigned discrete curvature is maximal; ties are resolved by the least original grid index.

Facts & Assumptions

Given: A real matrix, a data vector, and a strictly increasing finite positive parameter grid with at least three points, as specified in Discrete maximum-curvature L-curve parameter selection.

[F1]

Discrete maximum-curvature L-curve parameter selection: The procedure computes finitely many Tikhonov solutions, discards points with a zero residual or solution norm, and returns failure if fewer than three points remain; otherwise it computes one finite curvature for each interior retained point and selects a maximum, using the least original index to break ties.

Proof

1.1givenF1algebra

The input grid has finite length q. Each positive parameter gives an invertible matrix ATA+λjI because zT(ATA+λjI)z=∥Az∥2+λj∥z∥2>0 for z≠0. Thus the solution and residual calculations in [F1] are defined; a finite number of scalar norm, positivity, logarithm, determinant, and arithmetic operations determine the retained points and curvatures. Every loop terminates after at most q iterations.

2.1F1step 1.1algebra∎

If fewer than three points remain, [F1] returns the prescribed failure status. Otherwise the finite nonempty set of assigned curvature values has a maximum; the finite set of indices attaining it has a least original grid index. The tie rule in [F1] therefore returns a maximizer and terminates.

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