Testing strict monotonicity in nonparametric regression

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A new test for strict monotonicity of the regression function is proposed which is based on a composition of an estimate of the inverse of the regression function with a common regression estimate. This composition is equal to the identity if and only if the “true” regression function is strictly monotone, and a test based on an L2-distance is investigated. The asymptotic normality of the corresponding test statistic is established under the null hypothesis of strict monotonicity. AMS Subject Classification: 62G10

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Goodness-of-fit test, Nonparametric regression, Strictly monotone regression

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