{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T17:58:17Z","timestamp":1791395897623,"version":"4.3.3"},"reference-count":56,"publisher":"Institute of Mathematical Statistics","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Ann. Statist."],"published-print":{"date-parts":[[2024,10,1]]},"abstract":"<jats:p>This paper proposes a Gaussian process (GP) approach for testing conditional moment restrictions. Tests are based on squared Neyman orthogonal function-parametric processes integrated with respect to a GP distribution. This methodology leads to a general unified framework of kernel-based tests having the following properties: (i) bootstrap tests are easy to implement in the presence of nuisance parameters (they are simple quadratic forms, and there is no need to reestimate the nuisance parameters in each bootstrap replication); and (ii) the new tests are valid under general conditions, including higher-order conditional moments of unknown form, regularized estimators (e.g., Lasso) or parameters at the boundary of the parameter space. Novel applications include distance kernel tests for zero conditional treatment effects. The paper introduces Neyman orthogonal kernels, a new asymptotic theory and a detailed local power analysis. Monte Carlo experiments and a real data application illustrate the sensitivity of tests to the dimension of covariates and to the mean and covariance kernel of the GP.<\/jats:p>","DOI":"10.1214\/24-aos2443","type":"journal-article","created":{"date-parts":[[2024,11,21]],"date-time":"2024-11-21T01:31:34Z","timestamp":1732152694000},"page":"2456-2481","source":"Crossref","is-referenced-by-count":4,"title":["A Gaussian process approach to model checks"],"prefix":"10.1214","volume":"52","author":[{"given":"Juan Carlos","family":"Escanciano","sequence":"first","affiliation":[{"name":"Department of Economics, Universidad Carlos III de Madrid"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"108","reference":[{"key":"15","doi-asserted-by":"publisher","unstructured":"<small>Escanciano, J. C.<\/small> and <small>Velasco, C.<\/small> (2006). Generalized spectral tests for the martingale difference hypothesis. <i>J. Econometrics<\/i> <b>134<\/b> 151\u2013185.","DOI":"10.1016\/j.jeconom.2005.06.019"},{"key":"25","doi-asserted-by":"publisher","unstructured":"<small>HOFMANN, T.<\/small>, <small>SCH\u00d6LKOPF, B.<\/small> and <small>SMOLA, A. J.<\/small> (2008). Kernel methods in machine learning. <i>Ann. Statist.<\/i> <b>36<\/b> 1171\u20131220.","DOI":"10.1214\/009053607000000677"},{"key":"47","doi-asserted-by":"publisher","unstructured":"<small>STINCHCOMBE, M. B.<\/small> and <small>WHITE, H.<\/small> (1998). Consistent specification testing with nuisance parameters present only under the alternative. <i>Econometric Theory<\/i> <b>14<\/b> 295\u2013325.","DOI":"10.1017\/S0266466698143013"},{"key":"28","doi-asserted-by":"publisher","unstructured":"<small>JENNRICH, R. I.<\/small> (1969). Asymptotic properties of non-linear least squares estimators. <i>Ann. Math. Stat.<\/i> <b>40<\/b> 633\u2013643.","DOI":"10.1214\/aoms\/1177697731"},{"key":"36","doi-asserted-by":"publisher","unstructured":"<small>MUANDET, K.<\/small>, <small>FUKUMIZU, K.<\/small>, <small>SRIPERUMBUDUR, B.<\/small> and <small>SCH\u00d6LKOPF, B.<\/small> (2017). Kernel mean embedding of distributions: A review and beyond. <i>Found. Trends Mach. Learn.<\/i> <b>10<\/b> 1\u2013141.","DOI":"10.1561\/2200000060"},{"key":"38","unstructured":"<small>NEYMAN, J.<\/small> (1959). Optimal asymptotic tests of composite statistical hypotheses. In <i>Probability and Statistics<\/i>: <i>The Harald Cram\u00e9r Volume<\/i> (U. Grenander, ed.) 213\u2013234. Almqvist &amp; Wiksell, Stockholm."},{"key":"21","doi-asserted-by":"publisher","unstructured":"<small>GONZ\u00c1LEZ-MANTEIGA, W.<\/small> and <small>CRUJEIRAS, R. M.<\/small> (2013). An updated review of goodness-of-fit tests for regression models. <i>TEST<\/i> <b>22<\/b> 361\u2013411.","DOI":"10.1007\/s11749-013-0327-5"},{"key":"44","doi-asserted-by":"publisher","unstructured":"<small>Shao, X.<\/small> and <small>Zhang, J.<\/small> (2014). Martingale difference correlation and its use in high-dimensional variable screening. <i>J. Amer. Statist. Assoc.<\/i> <b>109<\/b> 1302\u20131318.","DOI":"10.1080\/01621459.2014.887012"},{"key":"51","doi-asserted-by":"publisher","unstructured":"<small>Sz\u00e9kely, G. J.<\/small>, <small>Rizzo, M. L.<\/small> and <small>Bakirov, N. K.<\/small> (2007). Measuring and testing dependence by correlation of distances. <i>Ann. Statist.<\/i> <b>35<\/b> 2769\u20132794.","DOI":"10.1214\/009053607000000505"},{"key":"9","doi-asserted-by":"publisher","unstructured":"<small>Dudley, R. M.<\/small> (1999). <i>Uniform Central Limit Theorems<\/i>. <i>Cambridge Studies in Advanced Mathematics<\/i> <b>63<\/b>. Cambridge Univ. Press, Cambridge.","DOI":"10.1017\/CBO9780511665622"},{"key":"27","doi-asserted-by":"publisher","unstructured":"<small>Janssen, A.<\/small> (2000). Global power functions of goodness of fit tests. <i>Ann. Statist.<\/i> <b>28<\/b> 239\u2013253.","DOI":"10.1214\/aos\/1016120371"},{"key":"43","doi-asserted-by":"publisher","unstructured":"<small>Sejdinovic, D.<\/small>, <small>Sriperumbudur, B.<\/small>, <small>Gretton, A.<\/small> and <small>Fukumizu, K.<\/small> (2013). Equivalence of distance-based and RKHS-based statistics in hypothesis testing. <i>Ann. Statist.<\/i> <b>41<\/b> 2263\u20132291.","DOI":"10.1214\/13-AOS1140"},{"key":"1","doi-asserted-by":"publisher","unstructured":"<small>BARINGHAUS, L.<\/small> and <small>FRANZ, C.<\/small> (2004). On a new multivariate two-sample test. <i>J. Multivariate Anal.<\/i> <b>88<\/b> 190\u2013206.","DOI":"10.1016\/S0047-259X(03)00079-4"},{"key":"22","unstructured":"<small>GRETTON, A.<\/small>, <small>BORGWARDT, K. M.<\/small>, <small>RASCH, M. J.<\/small>, <small>SCH\u00d6LKOPF, B.<\/small> and <small>SMOLA, A.<\/small> (2012). A kernel two-sample test. <i>J. Mach. Learn. Res.<\/i> <b>13<\/b> 723\u2013773."},{"key":"31","doi-asserted-by":"publisher","unstructured":"<small>KIM, I.<\/small>, <small>BALAKRISHNAN, S.<\/small> and <small>WASSERMAN, L.<\/small> (2020). Robust multivariate nonparametric tests via projection averaging. <i>Ann. Statist.<\/i> <b>48<\/b> 3417\u20133441.","DOI":"10.1214\/19-AOS1936"},{"key":"23","doi-asserted-by":"publisher","unstructured":"<small>H\u00c4RDLE, W.<\/small> and <small>MAMMEN, E.<\/small> (1993). Comparing nonparametric versus parametric regression fits. <i>Ann. Statist.<\/i> <b>21<\/b> 1926\u20131947.","DOI":"10.1214\/aos\/1176349403"},{"key":"35","doi-asserted-by":"publisher","unstructured":"<small>MAMMEN, E.<\/small> (1993). Bootstrap and wild bootstrap for high-dimensional linear models. <i>Ann. Statist.<\/i> <b>21<\/b> 255\u2013285.","DOI":"10.1214\/aos\/1176349025"},{"key":"53","doi-asserted-by":"crossref","unstructured":"<small>Tibshirani, R.<\/small> (1996). Regression shrinkage and selection via the lasso. <i>J. Roy. Statist. Soc. Ser. B<\/i> <b>58<\/b> 267\u2013288.","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"key":"54","doi-asserted-by":"publisher","unstructured":"<small>van der Vaart, A. W.<\/small> (1998). <i>Asymptotic Statistics<\/i>. <i>Cambridge Series in Statistical and Probabilistic Mathematics<\/i> <b>3<\/b>. Cambridge Univ. Press, Cambridge.","DOI":"10.1017\/CBO9780511802256"},{"key":"26","doi-asserted-by":"publisher","unstructured":"<small>Imbens, G. W.<\/small> and <small>Rubin, D. B.<\/small> (2015). <i>Causal Inference\u2014for Statistics, Social, and Biomedical Sciences<\/i>: <i>An Introduction<\/i>. Cambridge Univ. Press, New York.","DOI":"10.1017\/CBO9781139025751"},{"key":"32","doi-asserted-by":"publisher","unstructured":"<small>Knight, K.<\/small> and <small>Fu, W.<\/small> (2000). Asymptotics for lasso-type estimators. <i>Ann. Statist.<\/i> <b>28<\/b> 1356\u20131378.","DOI":"10.1214\/aos\/1015957397"},{"key":"5","unstructured":"<small>Billingsley, P.<\/small> (2013). <i>Convergence of Probability Measures<\/i>. Wiley, New York."},{"key":"20","doi-asserted-by":"crossref","unstructured":"<small>Gin\u00e9, E.<\/small> and <small>Zinn, J.<\/small> (1990). Bootstrapping general empirical measures. <i>Ann. Probab.<\/i> <b>18<\/b> 851\u2013869.","DOI":"10.1214\/aop\/1176990862"},{"key":"49","doi-asserted-by":"publisher","unstructured":"<small>Stute, W.<\/small> (1997). Nonparametric model checks for regression. <i>Ann. Statist.<\/i> <b>25<\/b> 613\u2013641.","DOI":"10.1214\/aos\/1031833666"},{"key":"7","doi-asserted-by":"crossref","unstructured":"<small>CRUMP, R. K.<\/small>, <small>HOTZ, V. J.<\/small>, <small>IMBENS, G. W.<\/small> and <small>MITNIK, O. A.<\/small> (2008). Nonparametric tests for treatment effect heterogeneity. <i>Rev. Econ. Stat.<\/i> <b>90<\/b> 389\u2013405.","DOI":"10.1162\/rest.90.3.389"},{"key":"2","doi-asserted-by":"publisher","unstructured":"<small>BICKEL, P. J.<\/small>, <small>RITOV, Y.<\/small> and <small>STOKER, T. M.<\/small> (2006). Tailor-made tests for goodness of fit to semiparametric hypotheses. <i>Ann. Statist.<\/i> <b>34<\/b> 721\u2013741.","DOI":"10.1214\/009053606000000137"},{"key":"45","unstructured":"<small>SRIPERUMBUDUR, B. K.<\/small>, <small>FUKUMIZU, K.<\/small> and <small>LANCKRIET, G. R. G.<\/small> (2011). Universality, characteristic kernels and RKHS embedding of measures. <i>J. Mach. Learn. Res.<\/i> <b>12<\/b> 2389\u20132410."},{"key":"55","doi-asserted-by":"publisher","unstructured":"<small>VAN DER VAART, A. W.<\/small> and <small>WELLNER, J. A.<\/small> (2023). <i>Weak Convergence and Empirical Processes\u2014with Applications to Statistics<\/i>. <i>Springer Series in Statistics<\/i>. Springer, Cham.","DOI":"10.1007\/978-3-031-29040-4"},{"key":"6","doi-asserted-by":"publisher","unstructured":"<small>CHOI, S.<\/small>, <small>HALL, W. J.<\/small> and <small>SCHICK, A.<\/small> (1996). Asymptotically uniformly most powerful tests in parametric and semiparametric models. <i>Ann. Statist.<\/i> <b>24<\/b> 841\u2013861.","DOI":"10.1214\/aos\/1032894469"},{"key":"3","doi-asserted-by":"publisher","unstructured":"<small>BIERENS, H. J.<\/small> (1982). Consistent model specification tests. <i>J. Econometrics<\/i> <b>20<\/b> 105\u2013134.","DOI":"10.1016\/0304-4076(82)90105-1"},{"key":"4","doi-asserted-by":"publisher","unstructured":"<small>BIERENS, H. J.<\/small> and <small>PLOBERGER, W.<\/small> (1997). Asymptotic theory of integrated conditional moment tests. <i>Econometrica<\/i> <b>65<\/b> 1129\u20131151.","DOI":"10.2307\/2171881"},{"key":"8","doi-asserted-by":"crossref","unstructured":"<small>DELGADO, M. A.<\/small>, <small>DOMINGUEZ, M. A.<\/small> and <small>LAVERGNE, P.<\/small> (2006). Consistent tests of conditional moment restrictions\u201d. <i>Ann. \u00c9con. Stat.<\/i> <b>81<\/b> 33\u201367.","DOI":"10.2307\/20079138"},{"key":"10","doi-asserted-by":"publisher","unstructured":"<small>ESCANCIANO, J. C.<\/small> (2006). A consistent diagnostic test for regression models using projections. <i>Econometric Theory<\/i> <b>22<\/b> 1030\u20131051.","DOI":"10.1017\/S0266466606060506"},{"key":"11","doi-asserted-by":"publisher","unstructured":"<small>ESCANCIANO, J. C.<\/small> (2009). On the lack of power of omnibus specification tests. <i>Econometric Theory<\/i> <b>25<\/b> 162\u2013194.","DOI":"10.1017\/S0266466608090051"},{"key":"12","unstructured":"<small>ESCANCIANO, J. C.<\/small> (2009). Simple bootstrap tests for conditional moment restrictions. Mimeo. Available at <a href=\"http:\/\/www.ecares.org\/ecaresdocuments\/seminars0809\/escanciano.pdf\">http:\/\/www.ecares.org\/ecaresdocuments\/seminars0809\/escanciano.pdf<\/a>."},{"key":"13","doi-asserted-by":"publisher","unstructured":"<small>ESCANCIANO, J. C.<\/small> and <small>GOH, S. C.<\/small> (2014). Specification analysis of linear quantile models. <i>J. Econometrics<\/i> <b>178<\/b> 495\u2013507.","DOI":"10.1016\/j.jeconom.2013.07.006"},{"key":"14","unstructured":"<small>ESCANCIANO, J. C.<\/small>, <small>SANT\u2019ANNA, P. H.<\/small> and <small>SONG, X.<\/small> (2023). Specification tests for generalized propensity scores using double projections. Preprint. Available at arXiv:<a href=\"https:\/\/arxiv.org\/abs\/2003.13803\">2003.13803<\/a>."},{"key":"16","doi-asserted-by":"publisher","unstructured":"<small>FAN, Y.<\/small> and <small>LI, Q.<\/small> (2000). Consistent model specification tests: Kernel-based tests versus Bierens\u2019 ICM tests. <i>Econometric Theory<\/i> <b>16<\/b> 1016\u20131041.","DOI":"10.1017\/S0266466600166083"},{"key":"17","unstructured":"<small>FERN\u00c1NDEZ, T.<\/small> and <small>RIVERA, N.<\/small> (2024). A general framework for the analysis of kernel-based tests. <i>J. Mach. Learn. Res.<\/i> <b>25<\/b> Paper No. [95], 40 pp."},{"key":"18","doi-asserted-by":"publisher","unstructured":"<small>FERREIRA, J. C.<\/small> and <small>MENEGATTO, V. A.<\/small> (2013). Positive definiteness, reproducing kernel Hilbert spaces and beyond. <i>Ann. Funct. Anal.<\/i> <b>4<\/b> 64\u201388.","DOI":"10.15352\/afa\/1399899838"},{"key":"19","unstructured":"<small>FINKELSTEIN, A.<\/small>, <small>TAUBMAN, S.<\/small>, <small>WRIGHT, B.<\/small>, <small>BERNSTEIN, M.<\/small>, <small>GRUBER, J.<\/small>, <small>NEWHOUSE, J. P.<\/small>, <small>ALLEN, H.<\/small>, <small>BAICKER, K.<\/small> and <small>OREGON HEALTH STUDY GROUP<\/small> (2012). The Oregon health insurance experiment: Evidence from the first year. <i>Q. J. Econ.<\/i> <b>127<\/b> 1057\u20131106."},{"key":"24","doi-asserted-by":"publisher","unstructured":"<small>HEISS, F.<\/small>, <small>HETZENECKER, S.<\/small> and <small>OSTERHAUS, M.<\/small> (2022). Nonparametric estimation of the random coefficients model: An elastic net approach. <i>J. Econometrics<\/i> <b>229<\/b> 299\u2013321.","DOI":"10.1016\/j.jeconom.2020.11.010"},{"key":"29","unstructured":"<small>KANAGAWA, M.<\/small>, <small>HENNIG, P.<\/small>, <small>SEJDINOVIC, D.<\/small> and <small>SRIPERUMBUDUR, B. K.<\/small> (2018). Gaussian processes and kernel methods: a review on connections and equivalences. Preprint. Available at arXiv:<a href=\"https:\/\/arxiv.org\/abs\/1807.02582\">1807.02582<\/a>."},{"key":"30","doi-asserted-by":"crossref","unstructured":"<small>KHMALADZE, \u00c8. V.<\/small> (1981). A martingale approach in the theory of goodness-of-fit tests. <i>Teor. Veroyatn. Primen.<\/i> <b>26<\/b> 246\u2013265.","DOI":"10.1137\/1126027"},{"key":"33","doi-asserted-by":"publisher","unstructured":"<small>LINDSAY, B. G.<\/small>, <small>MARKATOU, M.<\/small> and <small>RAY, S.<\/small> (2014). Kernels, degrees of freedom, and power properties of quadratic distance goodness-of-fit tests. <i>J. Amer. Statist. Assoc.<\/i> <b>109<\/b> 395\u2013410.","DOI":"10.1080\/01621459.2013.836972"},{"key":"34","doi-asserted-by":"publisher","unstructured":"<small>LINDSAY, B. G.<\/small>, <small>MARKATOU, M.<\/small>, <small>RAY, S.<\/small>, <small>YANG, K.<\/small> and <small>CHEN, S.-C.<\/small> (2008). Quadratic distances on probabilities: A unified foundation. <i>Ann. Statist.<\/i> <b>36<\/b> 983\u20131006.","DOI":"10.1214\/009053607000000956"},{"key":"37","unstructured":"<small>MUANDET, K.<\/small>, <small>JITKRITTUM, W.<\/small> and <small>K\u00dcBLER, J.<\/small> (2020). Kernel conditional moment test via maximum moment restriction. In <i>Conference on Uncertainty in Artificial Intelligence<\/i> 41\u201350."},{"key":"39","unstructured":"<small>OKUTMUSTUR, B.<\/small> and <small>GHEONDEA, A.<\/small> (2010). <i>Reproducing Kernel Hilbert Spaces. The Basics Bergman Spaces and Interpolation Problems<\/i>. LAP LAMBERT Academic Publishing."},{"key":"40","doi-asserted-by":"crossref","unstructured":"<small>ROSENBAUM, P. R.<\/small> and <small>RUBIN, D. B.<\/small> (1983). Assessing sensitivity to an unobserved binary covariate in an observational study with binary outcome. <i>J. R. Stat. Soc. Ser. B. Stat. Methodol.<\/i> <b>45<\/b> 212\u2013218.","DOI":"10.1111\/j.2517-6161.1983.tb01242.x"},{"key":"41","doi-asserted-by":"publisher","unstructured":"<small>SANCETTA, A.<\/small> (2021). Estimation in reproducing Kernel Hilbert spaces with dependent data. <i>IEEE Trans. Inf. Theory<\/i> <b>67<\/b> 1782\u20131795.","DOI":"10.1109\/tit.2020.3045290"},{"key":"42","doi-asserted-by":"publisher","unstructured":"<small>SANCETTA, A.<\/small> (2022). Testing subspace restrictions in the presence of high dimensional nuisance parameters. <i>Electron. J. Stat.<\/i> <b>16<\/b> 5277\u20135320.","DOI":"10.1214\/22-ejs2058"},{"key":"46","doi-asserted-by":"publisher","unstructured":"<small>STEINWART, I.<\/small> (2019). Convergence types and rates in generic Karhunen-Lo\u00e8ve expansions with applications to sample path properties. <i>Potential Anal.<\/i> <b>51<\/b> 361\u2013395.","DOI":"10.1007\/s11118-018-9715-5"},{"key":"48","doi-asserted-by":"crossref","unstructured":"<small>STRASSER, H.<\/small> (1990). Global extrapolation of local efficiency. <i>Statist. Decisions<\/i> <b>8<\/b> 11\u201326.","DOI":"10.1524\/strm.1990.8.1.11"},{"key":"50","doi-asserted-by":"publisher","unstructured":"<small>STUTE, W.<\/small>, <small>GONZ\u00c1LEZ MANTEIGA, W.<\/small> and <small>PRESEDO QUINDIMIL, M.<\/small> (1998). Bootstrap approximations in model checks for regression. <i>J. Amer. Statist. Assoc.<\/i> <b>93<\/b> 141\u2013149.","DOI":"10.2307\/2669611"},{"key":"52","doi-asserted-by":"publisher","unstructured":"<small>TAN, F.<\/small> and <small>ZHU, L.<\/small> (2022). Integrated conditional moment test and beyond: When the number of covariates is divergent. <i>Biometrika<\/i> <b>109<\/b> 103\u2013122.","DOI":"10.1093\/biomet\/asab009"},{"key":"56","doi-asserted-by":"publisher","unstructured":"<small>WU, C.-F. J.<\/small> (1986). Jackknife, bootstrap and other resampling methods in regression analysis. <i>Ann. Statist.<\/i> <b>14<\/b> 1261\u20131350. With discussion and a rejoinder by the author.","DOI":"10.1214\/aos\/1176350142"}],"container-title":["The Annals of Statistics"],"original-title":[],"deposited":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T17:27:59Z","timestamp":1791394079000},"score":1,"resource":{"primary":{"URL":"https:\/\/projecteuclid.org\/journals\/annals-of-statistics\/volume-52\/issue-5\/A-Gaussian-process-approach-to-model-checks\/10.1214\/24-AOS2443.full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,1]]},"references-count":56,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2024,10,1]]}},"URL":"https:\/\/doi.org\/10.1214\/24-aos2443","relation":{},"ISSN":["0090-5364","2168-8966"],"issn-type":[{"value":"0090-5364","type":"print"},{"value":"2168-8966","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,1]]}}}