การประมาณค่าพารามิเตอร์ในการวิเคราะห์ความถดถอยพหุนามเมื่อมีความคลาดเคลื่อนเกิดขึ้นในตัวแปรอิสระ - ธิฏิรัตน์ เมฆบัณฑิตกุล (จุฬาลงกรณ์มหาวิทยาลัย, 2003)
The purpose of this research is to com pare the method of parameter estimations in polynomial regression models with errors in independent variables by Ordinary least squares method (OLS) 1 Adjusted least squares method (ALS) and Weighted least squares method (WLS). The criterion of comparison is average relative root mean squares error (ARRMSE) and u se ratio of different average relative root mean squares error (RDARRMSE) to support decision. The distribution of random errors are normal distribution with mean equal to 0 and standard deviation equal to 0,1, 0.3, 0.5, 0.7 and 1.0, respectively. For the distribution of errors in independent variables are normal distribution with mean equal to 0 and standard deviation equal to 0.1, 0.3, 0.5 and 0.7, respectively. The sample sizes used in this study are 15, 30, 50, 100 and 200, respectivey, highest degree of independent variables for dependent variable building in mode (MB) are 2, 3, 4, 5 and 6, respectively. The data for this experiment are generated through the Monte Carlo simulation technique and repeating 1000 times for each ca se. The results of this research are a s follow : The average relative root mean squares error vary with 1 most to least 1 respectively 1 highest degree of independent variables for dependent variable building in model (MB), standard deviation of errors in independent variables (℺δ), standard deviation of random errors (℺δ) but con verse to sample size (n). 1. In case of sample size is low (n = 15). If MB is low (MB = 2 ) , standard deviation of random errors (℺δ) and standard deviation of errors in independent variables (℺δ) are low (℺δ. ≤ 0.3 and ℺δ ≤ 0.3) the OLS method is the best, the ALS method and the WLS method , respectively. Except in ca se standard deviation of random errors (℺δ) and standard deviation of errors in independent variables (℺δ) equal to 0.3 the ALS method is the best , the WLS method and the OLS method , respectively. When standard deviation of random errors(℺δ) and standard deviation of errors in independent variables (℺δ) are medium to high (℺δ. ≤ 0.5 and ℺δ ≤ 0.5), the WLS method is the best; the ALS method and the OLS method , respectively 2. In case of sample size is medium to high (n > 15). If MB is medium to high (MB > 2), for all standard deviation of random errors (℺δ) and standard deviation of errors in independent variables (℺δ), the WLS method is the best, the ALS method and the OLS method, respectively.