1 citations · 2 across the 8 of their papers we have counts for
4 papers · 1 filter
Piece-wise linear isotonic regression
Timo Kuosmanen, Juan F. Monge, José L. Ruiz +1
Isotonic regression provides a flexible, tuning-free approach to estimating monotonic functions without imposing global curvature constraints, yet the estimated regression function…
Overfitting Reduction in Convex Regression
Zhiqiang Liao, Sheng Dai, Eunji Lim +1
Convex regression is a method for estimating the convex function from a data set. This method has played an important role in operations research, economics, machine learning, and…
Modeling economies of scope in joint production: Convex regression of input distance function
Timo Kuosmanen, Sheng Dai
Modeling of joint production has proved a vexing problem. This paper develops a radial convex nonparametric least squares (CNLS) approach to estimate the input distance function wi…
Optimal resource allocation: Convex quantile regression approach
Sheng Dai, Natalia Kuosmanen, Timo Kuosmanen +1
Optimal allocation of resources across sub-units in the context of centralized decision-making systems such as bank branches or supermarket chains is a classical application of ope…