Corrigendum

Abstract

Statistical Analysis and Data Mining: The ASA Data Science JournalVolume 16, Issue 1 p. 92-92 CORRIGENDUMFree Access Corrigendum This article corrects the following: Neural network for univariate and multivariate nonlinearity tests Shapour Mohammadi, Volume 13Issue 1Statistical Analysis and Data Mining: The ASA Data Science Journal pages: 50-70 First Published online: November 18, 2019 First published: 21 November 2022 https://doi.org/10.1002/sam.11604AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat In Mohammadi [1], The authors regret to inform that the citation for the bds.m code written by Professor Ludwig Kanzler were not included to Table 1. The updated Table 1 note is shown below. Note: Tests are Lee, White, and Granger (LWG); Terasvirta, Lee, and Granger (TLG); Tsay; Brock, Dechert, and Sheinkman (BDS); MC Leod Li (MCLoLi); Ramsy; Keenan; and AutoRegressive Conditional Heteroscedasticity (ARCH). Data generating process are white noise (WN), first-order autoregressive (AR1), second-order autoregressive (AR2), second order moving average (MA2), third order moving average (MA3), fifth order moving average (MA5), autoregressive moving average of various orders (ARMA1,1; ARMA2,1; ARMA2,2 and ARMA2,3). SizDist stands for distortion of empirical size from nominal. The BDS p-values are computed by using the code developed by Ludwig Kanzler. Reference: L. Kanzler, BDS: MATLAB module to calculate Brock, Dechert & Scheinkman test for independence, Statistical Software Components T871803, Boston College Department of Economics, Massachusetts, 1998. REFERENCE 1S. Mohammadi, Neural network for univariate and multivariate nonlinearity tests. Stat. Anal. Data Mining ASA Data Sci. J. 13 (2019), 9250– 9270. Volume16, Issue1February 2023Pages 92-92 ReferencesRelatedInformation