A variable selection approach to monotonic regression with Bernstein polynomials

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Most Likely Transformations (2015, background): “This choice is computationally attractive because strict monotonicity can be formulated as a set of M linear constraints on the parameters ϑm ϑm+1 for all m = 0, . . . ,M (Curtis and Ghosh 2011).”