{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T04:48:56Z","timestamp":1758862136981},"reference-count":11,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2014,1,27]],"date-time":"2014-01-27T00:00:00Z","timestamp":1390780800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J of Applied Econometrics"],"published-print":{"date-parts":[[2014,3]]},"abstract":"SUMMARY<\/jats:title>crs<\/jats:styled-content> is a library for R<\/jats:styled-content> written by Jeffrey S. Racine (Maintainer) and Zhenghua Nie. This add\u2010on package provides a collection of functions for spline\u2010based nonparametric estimation of regression functions with both continuous and categorical regressors. Currently, the crs<\/jats:styled-content> package integrates data\u2010driven methods for selecting the spline degree, the number of knots and the necessary bandwidths for nonparametric conditional mean, IV and quantile regression. A function for multivariate density spline estimation with mixed data is also currently in the works. As a bonus, the authors have also provided the first simple R<\/jats:styled-content> interface to the NOMAD<\/jats:styled-content> (\u2018nonsmooth mesh adaptive direct search\u2019) optimization solver which can be applied to solve other mixed integer optimization problems that future users might find useful in other settings. Although the crs<\/jats:styled-content> package shares some of the same functionalities as its kernel\u2010based counterpart\u2014the np<\/jats:styled-content> package by the same author\u2014it currently lacks some of the features the np<\/jats:styled-content> package provides, such as hypothesis testing and semiparametric estimation. However, what it lacks in breadth, crs<\/jats:styled-content> makes up in speed. A Monte Carlo experiment in this review uncovers sizable speed gains compared to its np<\/jats:styled-content> counterpart, with a marginal loss in terms of goodness of fit. Therefore, the package will be extremely useful for applied econometricians interested in employing nonparametric techniques using large amounts of data with a small number of discrete covariates. Copyright \u00a9 2014 John Wiley & Sons, Ltd.<\/jats:p>","DOI":"10.1002\/jae.2381","type":"journal-article","created":{"date-parts":[[2014,1,28]],"date-time":"2014-01-28T03:56:59Z","timestamp":1390881419000},"page":"348-352","source":"Crossref","is-referenced-by-count":3,"title":["crs: A PACKAGE FOR NONPARAMETRIC SPLINE ESTIMATION IN R"],"prefix":"10.1002","volume":"29","author":[{"given":"Anson T.Y.","family":"Ho","sequence":"first","affiliation":[{"name":"Department of Economics Kansas State University Manhattan KS USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kim P.","family":"Huynh","sequence":"additional","affiliation":[{"name":"Currency Department Bank of Canada Ottawa Ontario Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David T.","family":"Jacho\u2010Ch\u00e1vez","sequence":"additional","affiliation":[{"name":"Department of Economics Emory University Atlanta GA USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2014,1,27]]},"reference":[{"key":"e_1_2_5_2_1","unstructured":"AbramsonM AudetC CoutureG DennisJ Jr Le DigabelS TribesC2011.The NOMAD project. 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