We study a regression problem where for some part of the data we observe both label variable (Y) and predictors (X), while other only are given. Such arises, example, when observations costly may require skilled human agent. When conditional expectation E[Y|X] is not exactly linear, one can consider best linear approximation to expectation, which be estimated consistently by least-square estima...

This study compares the proposed hybrid method (wavelet robust M-estimation) to traditional ordinary least square) when there are de-noising or outlier problems for estimating multiple linear regression models using statistical criterion root mean square error (RMSE). According simulated and real data, is better than classical (Wavelet Ordinary Least Square) more accurate. The of less Wavelet S...