Journal
JOURNAL OF STATISTICAL PLANNING AND INFERENCE
Volume 188, Issue -, Pages 8-21Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jspi.2017.03.007
Keywords
Mode estimation; Inflection point; Monotone; Convex; Convergence rate
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We consider estimating a regression function f(m) and a change-point m, where m is a mode or an inflection point. For a given m, the least-squares estimate of fm is found using constrained regression splines, then the set of possible change-points is searched to find the overall least-squares (m) over cap Convergence rates are obtained for each type of change-point estimator, and simulations show that these methods compare well to existing methods. Extensions to the partial linear model and to the case of correlated errors are straightforward, and a penalized spline version is also provided. The methods are available in the R package ShapeChange. (C) 2017 Elsevier B.V. All rights reserved.
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