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Testing nonparametric shape restrictions

Tatiana Komarova, Javier Hidalgo

arXiv 4 Sep 2019 · Statistics — Methodology · publishedThe Annals of Statistics (2023) · 4 citations (OpenAlex)

arXiv:1909.01675 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We describe and examine a test for a general class of shape constraints, such as constraints on the signs of derivatives, U-(S-)shape, symmetry, quasi-convexity, log-convexity, $r$-convexity, among others, in a nonparametric framework using partial sums empirical processes. We show that, after a suitable transformation, its asymptotic distribution is a functional of the standard Brownian motion, so that critical values are available. However, due to the possible poor approximation of the asymptotic critical values to the finite sample ones, we also describe a valid bootstrap algorithm.

Citation extraction

93
references
147
in-text mentions
92
distinct cited
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self-citations
19,581
main-text words

appendix boundary found by appendix_titled_section at “\textbf{APPENDIX A}” · 60% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Ghosal, S., Sen, A. and van der Vaart, A (2000) Testing monotonicity of regression0.87472100%
2Stute, W (1997) Nonparametric model checks for regression0.87452100%
3Brown, R.L., Durbin, J. and Evans, J.M (1975) Techniques for testing the constancy of regression relationships over time (with discussion)0.81142100%
4Hall, P. and Heckman, N. E (2000) Testing for Monotonicity of a Regression Mean by Calibrating for Linear Functions0.81142100%
5Khmaladze, E.V (1981) Martingale approach to the theory of goodness of fit tests0.81142100%
6Bowman, A.W., Jones, M.C. and Gijbels, I (1998) Testing monotonicity of regression0.73732100%
7Agarwal, G.G. and Studden, W.J (1980) Asymptotic Integrated Mean Square Error Using Least Squares and Bias Minimizing Splines0.6444250%
8Andrews, D.W.K (1997) A Conditional Kolmogorov Test0.64422100%
9Brunk, H. D (1955) Maximum likelihood estimates of monotone parameters0.64422100%
10Durbin, J (1973) Distribution Theory for Tests Based on the Sample Distribution Function0.64422100%

Showing the top 10 of 92 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1A Projection Framework for Testing Shape Restrictions That Form Convex Cones0.51121
2A Unifying Framework for Testing Shape Restrictions0.40511
3Testing Shape Restrictions with Continuous Treatment: A Transformation Model Approach0.40511