weighted least-squares approach
An adapted version of the element wise weighted total least squares method for applications in chemometrics
... EW-TLS approach is not the right method of choice for the case when m≤ n and only row-wise correlated measure- ments and we have pointed out that the EW-TLS approach needed to be adapted for handling this ...
7
Empirical likelihood based inference in Poisson autoregressive model with conditional moment restrictions
... our approach proposed, compared to the maximum likelihood estimator, the least squares estimator, and the weighted least squares estimator, yields more efficient ...
13
Partial Least Squares in Constructing Candidates Model Averaging Muhammad Arna Ramadhan, Bagus Sartono, Anang Kurnia
... is weighted average of several candidate models, in order to improve prediction ...partial least squares model averaging (PLSMA) as an approach to construct candidate models, while partial ...
5
The element wise weighted total least squares problem
... The parameter estimation problem is typically defined as an optimization problem: an appropriate cost function depending on the data is minimized over the estimated param- eters. The classical approach, the ...
29
A Constrained Least Squares Approach to Mobile Positioning: Algorithms and Optimality
... nonlinear least squares (NLS) or weighted least squares (WLS) ...latter approach is adopted, and we will focus on a unified de- velopment of accurate location algorithms, given ...
23
Particle Swarm Optimization and Differentiation Evolution –Based Weighted Least Squares State Estimation
... The Weighted Least Square (WLS) method is the commonly used state estimation approach which is used in power industries [17, ...paper weighted least square algorithm along with flow ...
8
Robust Regression Analysis with LR Type Fuzzy Input Variables and Fuzzy Output Variable
... the Weighted Least Squares (WLS) ...the Least Median Squares and the Weighted Least Squares (LMS-WLS) approach, we give steps of the LMS-WLS estimation ...
17
An extension of RSS-based model comparison tests for weighted least squares
... ordinary least squares framework, we reviewed assumptions and theorems which form the basis for a rigorous quantitative theory of model comparison based upon the statistical properties of least ...
19
A weighted least squares solution for space intersection of spaceborne stereo SAR data
... SAR approach is a promising tool for producing DEMs from spaceborne SAR data ...analytic approach to carry out space intersection by using a least squares adjustment for ERS-1 data and ...
8
Tree Based Orthogonal Least Squares Regression with Repeated Weighted Boosting Search
... Abstract—Orthogonal Least Squares Regression (OLSR) selects each regressor by repeated weighted boosting search (RWBS). This kind of OLSR is known to be capable of producing a much sparser model than ...
9
On weighted structured total least squares
... Abstract. In this contribution we extend our previous results on the structured total least squares problem to the case of weighted cost func- tions. It is shown that the computational complexity of ...
8
Teaching Least Squares in Matrix Notation
... The least squares method, a fundamental piece of knowledge for students of all scientific tracks, is often introduced considering the simple linear regression with only two parameters to be ...the ...
13
An alternative approach to approximating the moments of least squares estimators
... A new methodology is presented for approximating the moments of least squares coefficient estimators in situations where endogene- ity and dynamics are present. The OLS estimator is the focus here, but the ...
24
Timing of Cortical Activation: A Latency Resolved Event Related Functional MR Imaging Study
... averaging approach as used in several studies is valid and more reliable because alignment of the fMRI response can be made to the presentation of the visual ...
8
Standard and proportional error model comparison for logistic growth of green algae (Raphidocelis subcapiala)
... A more general methodology motivated by the weighted least squares (as we have presented it in [2]) involves the so-called Generalized Least Squares (GLS) estimator.. Standard residuals [r] ...
21
Overview of total least squares methods
... total least squares problems [12], the data matrix A B is ...total least squares problem formulation is ex- tended [31] with the additional constraint that the structure of the data matrix A B ...
24
A Simulation-based Portfolio Optimization Approach with Least Squares Learning
... numerical approach that is based on the Least Squares Monte Carlo method to calculate the conditional value functions of investors for a sequence of discrete decision ...
6
Approximate Least Squares Accelerator
... with least significant bits of other 2x2 blocks to enable more compression and reduce the height of the partial product matrix by a factor of ...the least ap- proximate design of this method has a very ...
108
Derivative Estimation Based on Difference Sequence via Locally Weighted Least Squares Regression
... Our method and the local polynomial regression (LPR) have a close relationship. Both methods rely on Taylor expansion and employ the idea of locally weighted fitting. However, there are important differences ...
25
Predicting the quality of ryegrass using hyperspectral imaging
... This study examines the utility of Hyperspectral Imag- ing (HSI) based methods for non-invasive assessment of the composition of ryegrass. The quality of forage is an important component of animal performance and envi- ...
12