Pages that link to "Item:Q3334807"

The following pages link to The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses (Q3334807):

Displaying 50 items.

• A new universal resample-stable bootstrap-based stopping criterion for PLS component construction (Q123736) (← links)
• Partial least squares with a regularized weight (Q283784) (← links)
• On the exploration of linear latent effect for multivariate modeling (Q345510) (← links)
• Multi-output learning via spectral filtering (Q439000) (← links)
• Integrating spectral clustering with wavelet based kernel partial least square regressions for financial modeling and forecasting (Q632930) (← links)
• A comparison of various methods for multivariate regression with highly collinear variables (Q635880) (← links)
• Supervised principal component analysis: visualization, classification and regression on subspaces and submanifolds (Q716365) (← links)
• Partial least-squares vs. Lanczos bidiagonalization. I: Analysis of a projection method for multiple regression (Q956896) (← links)
• PLS regression on a stochastic process (Q957099) (← links)
• Interpretation of partial least-squares regression models with VARIMAX rotation (Q957103) (← links)
• Clusterwise PLS regression on a stochastic process (Q957186) (← links)
• Convex multi-task feature learning (Q1009294) (← links)
• A bidiagonalization algorithm for solving large and sparse ill-posed systems of linear equations (Q1111337) (← links)
• Stability of the inverse correlation matrix. Partial ridge regression (Q1298948) (← links)
• Methods and algorithms of solving spectral problems for polynomial and rational matrices (Q1389295) (← links)
• A decision rule for discarding principal components in regression (Q1582370) (← links)
• Numerical methods and questions in the organization of calculus. XII. Transl. from the Russian (Q1594772) (← links)
• An exposition of multivariate analysis with the singular value decomposition in R (Q1623402) (← links)
• \(l_{0}\)-norm based structural sparse least square regression for feature selection (Q1669627) (← links)
• Kernel negative \(\varepsilon\) dragging linear regression for pattern classification (Q1693779) (← links)
• How to choose biomarkers in view of parameter estimation (Q1711958) (← links)
• Dimension reduction in the linear model for right-censored data: Predicting the change of HIV-I RNA levels using clinical and Protease gene mutation data (Q1770871) (← links)
• Nonlinear black-box modeling in system identification: A unified overview (Q1911270) (← links)
• A weighted view on the partial least-squares algorithm (Q1977038) (← links)
• Approximate kernel partial least squares (Q2023883) (← links)
• Approximation algorithms for the lower-bounded knapsack median problem (Q2039651) (← links)
• Nonlinear transformation on the transfer entropy of financial time series (Q2147662) (← links)
• Surrogate modeling of high-dimensional problems via data-driven polynomial chaos expansions and sparse partial least square (Q2180429) (← links)
• A data envelopment analysis and local partial least squares approach for identifying the optimal innovation policy direction (Q2184060) (← links)
• PLS-based adaptation for efficient PCE representation in high dimensions (Q2220565) (← links)
• PLS for Big Data: a unified parallel algorithm for regularised group PLS (Q2323935) (← links)
• Computing Fréchet derivatives in partial least squares regression (Q2341895) (← links)
• Multi-class tumor classification by discriminant partial least squares using microarray gene expression data and assessment of classification models (Q2490602) (← links)
• Real-time reservoir management: a multiscale adaptive optimization and control approach (Q2496534) (← links)
• Borrowing information from relevant microarray studies for sample classification using weighted partial least squares (Q2500306) (← links)
• Mixed integer quadratic optimization formulations for eliminating multicollinearity based on variance inflation factor (Q2633546) (← links)
• OR forum: An algorithmic approach to linear regression (Q2806052) (← links)
• Convergence rates of kernel conjugate gradient for random design regression (Q2835985) (← links)
• Statistical corrections of invalid correlation matrices (Q2868869) (← links)
• PLS Typological Regression: Algorithmic, Classification and Validation Issues (Q3178556) (← links)
• On the structure of partial least squares regression (Q3471516) (← links)
• PLS: A versatile tool for industrial process improvement and optimization (Q3552653) (← links)
• Kernel partial least squares for stationary data (Q4637047) (← links)
• Study of partial least squares and ridge regression methods (Q4638853) (← links)
• Regression methods for high dimensional multicollinear data (Q4787632) (← links)
• Model order reduction using neural network principal component analysis and generalized dimensional analysis (Q4908018) (← links)
• VIF-based adaptive matrix perturbation method for heteroskedasticity-robust covariance estimators in the presence of multicollinearity (Q4976207) (← links)
• Bridging data exploration and modeling in event-history analysis: the supervised-component Cox regression (Q5035646) (← links)
• Variable selection under multicollinearity using modified log penalty (Q5036976) (← links)
• A simple way to deal with multicollinearity (Q5127052) (← links)