Chen, Fuqi; Nkurunziza, Sévérien Constrained inference in multiple regression with structural changes. (English) Zbl 1308.62051 Stat. Risk. Model. 31, No. 3-4, 237-257 (2014). Summary: In this paper, we study an inference problem for the regression coefficients in some multivariate regression models with multiple change-points occurring at unknown times, when the regression coefficients may satisfy some restrictions. The hypothesized restriction is more general than that given in recent literature. Under a weaker assumption than that given in recent literature, we derive the joint asymptotic normality of the restricted and unrestricted estimators. Finally, we construct a test for the hypothesized restriction and derive its asymptotic power. MSC: 62F30 Parametric inference under constraints 62J05 Linear regression; mixed models 62G10 Nonparametric hypothesis testing 62E20 Asymptotic distribution theory in statistics Keywords:asymptotic normality; change-points; least-squares estimator; mixingale; regression model; structural changes model PDFBibTeX XMLCite \textit{F. Chen} and \textit{S. Nkurunziza}, Stat. Risk. Model. 31, No. 3--4, 237--257 (2014; Zbl 1308.62051) Full Text: DOI