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  1. ; (, Theory of Probability and Mathematical Statistics)
    This article investigates some nice properties of the least squares estimator of the multivariate isotonic regression function (denoted as LSEMIR) when the model is misspecified and the errors are beta-mixing stationary random variables. Under mild conditions, it is observed that the least squares estimator converges uniformly to a certain monotone function, which is closest to the original function in an appropriate sense. 
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