6 citations · 9 across the 4 of their papers we have counts for
4 papers
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…
Convex Support Vector Regression
Zhiqiang Liao, Sheng Dai, Timo Kuosmanen
Nonparametric regression subject to convexity or concavity constraints is increasingly popular in economics, finance, operations research, machine learning, and statistics. However…
pyStoNED: A Python Package for Convex Regression and Frontier Estimation
Sheng Dai, Yu-Hsueh Fang, Chia-Yen Lee +1
Shape-constrained nonparametric regression is a growing area in econometrics, statistics, operations research, machine learning and related fields. In the field of productivity and…
Variable selection in convex quantile regression: L1-norm or L0-norm regularization?
Sheng Dai
The curse of dimensionality is a recognized challenge in nonparametric estimation. This paper develops a new L0-norm regularization approach to the convex quantile and expectile re…