Adaptive Approximation by Optimal Weighted Least-Squares Methods
نویسندگان
چکیده
منابع مشابه
Weighted Least Squares and Adaptive Least Squares: Further Empirical Evidence
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...
متن کاملGlicbawls - Grey Level Image Compression by Adaptive Weighted Least Squares
In recent years most research into lossless and near lossless compression of greyscale images could be characterized as belonging to either of two distinct groups The rst group which is concerned with so called practical algorithms encom passes research into methods that allow compression and decompression with low to moderate computational complexity while still obtaining impressive compressio...
متن کاملWeighted total least squares formulated by standard least squares theory
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...
متن کاملAccurate Solution of Weighted Least Squares by Iterative Methods
We consider the weighted least-squares (WLS) problem with a very ill-conditioned weight matrix. Weighted least-squares problems arise in many applications including linear programming, electrical networks, boundary value problems, and structures. Because of roundoo errors, standard iterative methods for solving a WLS problem with ill-conditioned weights may not give the correct answer. Indeed, ...
متن کاملLeast Squares Approximation by One-Pass Methods with Piecewise Polynomials
We propose several one-pass methods for data fitting in which a piecewise polynomial is used as an approximating function. The polynomial pieces are calculated step-by-step by the method of least squares as the data is -----------,scaIIIIed umy-once-from the begimring La tIre end. To calculate the least squares fitting in each step, we use three classes of data, namely: the data in the current ...
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: SIAM Journal on Numerical Analysis
سال: 2019
ISSN: 0036-1429,1095-7170
DOI: 10.1137/18m1198387