Estimate The Parameters in Presence of Multicollinearity And Outliers Using Bisquare Weighted Ridge Least Median Squares Regression (wrlms)
نویسندگان
چکیده
منابع مشابه
Weighted Ridge MM-Estimator in Robust Ridge Regression with Multicollinearity
This study is about the development of a robust ridge regression estimator. It is based on weighted ridge MM-estimator (WRMM) and is believed to have potentials in remedying the problems of multicollinearity. The proposed method has been compared with several existing estimators, namely ordinary least squares (OLS), robust regression based on MM estimator, ridge regression (RIDGE), weighted rid...
متن کاملLeast Median of Squares Regression
Classical least squares regression consists of minimizing the sum of the squared residuals. Many authors have produced more robust versions of this estimator by replacing the square by something else, such as the absolute value. In this article a different approach is introduced in which the sum is replaced by the median of the squared residuals. The resulting estimator can resist the effect of...
متن کاملThe Performance of Robust Weighted Least Squares in the Presence of Outliers and Heteroscedastic Errors
The Ordinary Least Squares (OLS) method is the most popular technique in statistics and is often use to estimate the parameters of a model because of tradition and ease of computation. The OLS provides an efficient and unbiased estimates of the parameters when the underlying assumptions, especially the assumption of contant error variances (homoscedasticity), are satisfied. Nonetheless, in real...
متن کاملWeighted Least Squares Scheme for Reducing Effects of Outliers in Regression based on Extreme Learning Machine
Neural networks have been massively used in regression problems due to their ability to approximate complex nonlinear mappings directly from input patterns. However, collected data for training networks often include outliers which affect final results. This paper presents an approach for training single hidden-layer feedforward neural networks (SLFNs) using weighted least-squares scheme which ...
متن کاملImproving plant biomass estimation in the field using partial least squares regression and ridge regression
Estimating primary productivity over time is challenging for plant ecologists. The most accurate biomass measurements require destructive sampling and weighing. This is often not possible for manipulative studies that involve repeatedmeasures over time, or for studies in protected areas. Estimates of aboveground plant biomass using allometric equations or linear regression on single plant trait...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Journal Of Duhok University
سال: 2020
ISSN: 1812-7568,2521-4861
DOI: 10.26682/sjuod.2020.23.2.2