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Automated image quality appraisal through partial least squares discriminant analysis
PurposeAutomatic retinal fundus image quality analysis is one of the most essential preliminary stages in automatic computer-aided retinal disease...
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Subsampling approach for least squares fitting of semi-parametric accelerated failure time models to massive survival data
Massive survival data are increasingly common in many research fields, and subsampling is a practical strategy for analyzing such data. Although...
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Least squares large margin distribution machine for regression
Better prediction ability is the main objective of any regression-based model. Large margin Distribution Machine for Regression (LDMR) is an...
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Enhancing quality of service in wireless systems using iterative weighted least squares with fuzzy logic integration algorithm
Effective quality of service (QoS) management is essential to the smooth running of wireless networks and to guarantee peak performance. This study...
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Quantitative Analysis of Methanol in Methanol Gasoline by Calibration Transfer Strategy Based on Kernel Domain Adaptive Partial Least Squares(kda-PLS)
The application of near-infrared(NIR) spectroscopy combined with multivariate calibration methods can achieve the rapid analysis of methanol...
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Application of Partial Least Squares Method Based on Big Data Analysis Technology in Sensor Error Compensation
In practice, uncertainties such as humidity and temperature cause unavoidable random errors in the sensor data. In order to reduce the error, a quick...
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Multiple Regression
In this chapter, we extend simple linear regression to include more than one explanatory variable. This alters the way we interpret our estimated...
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Tide modeling using partial least squares regression
This research explores the novel use of the partial least squares regression (PLSR) as an alternative model to the conventional least squares (LS)...
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Limited Memory BFGS Method for Least Squares Semidefinite Programming with Banded Structure
This work is intended to solve the least squares semidefinite program with a banded structure. A limited memory BFGS method is presented to solve...
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Downscaling GRACE total water storage change using partial least squares regression
The Gravity Recovery And Climate Experiment (GRACE) satellite mission recorded temporal variations in the Earth’s gravity field, which are then...
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The Consistency of LSE Estimators in Partial Linear Regression Models under Mixing Random Errors
In this paper, we consider the partial linear regression model y i = x i β * + g ( t i ) + ε i , i = 1, 2, …, n , where ( x i , t i ) are known fixed design points, g ...
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Fuzzy Transform and Least-Squares Fuzzy Transform: Comparison and Application
Fuzzy transform is a novel and well-founded soft computing method for reconstruction and denoising of image data. Recently, a least-squares fuzzy...
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Uncalibrated Visual Servoing Using Dynamic Broyden and Least-Squares Methods
Visual servo systems usually require a calibration operation before performing their tasks. This involves extra time cost, and the calibration...
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The Optimal Regularized Weighted Least-Squares Method for Impulse Response Estimation
The system identification literature has been going through a recent paradigm change with the emergent use of regularization and kernel-based...
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Discriminative least squares regression for multiclass classification based on within-class scatter minimization
Least square regression has been widely used in pattern classification, due to the compact form and efficient solution. However, two main issues...
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Functional Linear Partial Quantile Regression with Guaranteed Convergence for Neuroimaging Data Analysis
Functional data such as curves and surfaces have become more and more common with modern technological advancements. The use of functional predictors...
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Weighted-Average Least Squares (WALS): Confidence and Prediction Intervals
We consider inference for linear regression models estimated by weighted-average least squares (WALS), a frequentist model averaging approach with a...
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Bias Correction in the Least-Squares Monte Carlo Algorithm
This paper addresses the issue of foresight bias in the Longstaff and Schwartz (Rev Financ Stud 14(1):113–147, 2001) algorithm for American option...
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Partial Least Squares Structural Equation Modeling
Partial least squares structural equation modeling (PLS-SEM) has become a popular method for estimating path models with latent variables and their...
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Three-dimensional time-resolved Lagrangian flow field reconstruction based on constrained least squares and stable radial basis function
The three-dimensional time-resolved Lagrangian particle tracking (3D TR-LPT) technique has recently advanced flow diagnostics by providing high...
