登入選單

返回Google圖書搜尋

Revisiting the Evaluation of Robust Regression Techniques for Crop Yield Data Detrending

Robert Finger

出版	SSRN, 2020
URL	http://books.google.com.hk/books?id=7qXizwEACAAJ&hl=&source=gbs_api

註釋

Using a Monte Carlo experiment, the performance of the ordinary least squares (OLS) and the MM-estimator, a robust regression technique, is compared in an application of crop yield detrending. Assuming symmetric as well as skewed crop yield distributions, we show that the MM-estimator performs similarly to OLS for uncontaminated time series of crop yield data, and clearly outperforms OLS for outlier-contaminated samples. In contrast to earlier studies, our analysis suggests that robust regression techniques, such as the MM-estimator, should be reconsidered for detrending crop yield data.