This paper compares ordinary least squares (OLS), weighted least squares (WLS), and adaptive least squares (ALS) by means of a Monte Carlo study and an application to two empirical data sets. Overall, ALS emerges as the winner: It achieves most or even all of the efficiency gains of WLS over OLS when WLS outperforms OLS, but it only has very limited downside risk compared to OLS when OLS outper...

The purpose of this study is to introduce a new regression model, based on the least squares method, when the available data of both explanatory variable(s) and response variable are interval-valued fuzzy (IVF) numbers. The proposed method is based on a new metric on the space of IVF numbers, which is an extended version of the signed distance introduced by Yao and Wu (2000). In order to evalua...

This contribution presents a simple, attractive, and exible formulation for the weighted total least squares (WTLS) problem. It is simple because it is based on the well-known standard least squares theory; it is attractive because it allows one to directly use the existing body of knowledge of the least squares theory; and it is exible because it can be used to a broad eld of applications in t...