局部多项式和高次幂变换数据的前沿估计
Frontier estimation with local polynomials and high power-transformed data
摘要：
本文提出了一种新的估计样本前沿的方法。估计器是基于幂变换数据的局部多项式回归。我们假设变换的指数趋于无穷大，而带宽趋于零。我们给出了这两个参数的条件，以获得几乎完全收敛。给出了估计量的渐近条件偏差和方差，并在有限样本情形下说明了其良好的性能。
英文摘要：
We present a new method for estimating the frontier of a sample. The estimator is based on a local polynomial regression on the power-transformed data. We assume that the exponent of the transformation goes to infinity while the bandwidth goes to zero. We give conditions on these two parameters to obtain almost complete convergence. The asymptotic conditional bias and variance of the estimator are provided and its good performance is illustrated on some finite sample situations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
