Showing 1 - 4 of 4
equivalent to the initial unconstrained estimate if the regression function is in fact convex. If convexity is not present the …
Persistent link: https://www.econbiz.de/10010296683
In this paper we are concerned with shape restricted estimation in inverse regression problems with convolution-type operator. We use increasing rearrangements to compute increasingand convex estimates from an (in principle arbitrary) unconstrained estimate of the unknown regression function. An...
Persistent link: https://www.econbiz.de/10010298216
In this paper, a method for estimating monotone, convex and log-concave densities is proposed. The estimation procedure consists of an unconstrained kernel estimator which is modi?ed in a second step with respect to the desired shape constraint by using monotone rearrangements. It is shown that...
Persistent link: https://www.econbiz.de/10010300696
mean difference or the risk difference. By using convexity principles of the relevant composed functions and the moments of …
Persistent link: https://www.econbiz.de/10010316644