Add to ORKGThis paper presents some results about the asymptotic behaviour of the estimate of a regression model obtained by Partial Least Squares (PLS) Methods. Because the nonlinearity of the regression estimator on the response variable, local linear approximation through the 6-method for the PLS regression vector is carried out. A new implementation of the PLS algorithm is developed for this purpose
PLS regression methods have been used in applied fields for two decades. Techniques based on iterati...
High-dimensional datasets with a large number of explanatory variables are increasingly important in...
This paper derives the limiting distributions of least squares averaging estimators for linear regre...
This paper presents some results about the asymptotic behaviour of the estimate of a regression mod...
This paper presents some results about the asymptotic behaviour of the estimate of a regression mod...
This paper presents some results about the asymptotic behaviour of the estimate of a regression mod...
This paper presents some results about the asymptotic behaviour of the estimate of a regression mod...
AbstractIn this short note, we derive an expression for the asymptotic covariance matrix of the univ...
The Partial Least Squares approach (PLS) is a multivariate technique which was originated around 197...
Abstract Partial least squares (PLS) was first introduced by Wold in the mid 1960's as a heuris...
Let (X, B, Y) denote a random vector such that B and Y are real-valued, and X ∈ R2. Local linear est...
Let (X, B, Y) denote a random vector such that B and Y are real-valued, and X ∈ R2. Local linear est...
A vital extension to partial least squares (PLS) path modeling is introduced: consistency. While mai...
A vital extension to partial least squares (PLS) path modeling is introduced: consistency. While mai...
Partial Least Squares Regression (PLS-R) method is regression linear technique for multivariate pred...
PLS regression methods have been used in applied fields for two decades. Techniques based on iterati...
High-dimensional datasets with a large number of explanatory variables are increasingly important in...
This paper derives the limiting distributions of least squares averaging estimators for linear regre...
This paper presents some results about the asymptotic behaviour of the estimate of a regression mod...
This paper presents some results about the asymptotic behaviour of the estimate of a regression mod...
This paper presents some results about the asymptotic behaviour of the estimate of a regression mod...
This paper presents some results about the asymptotic behaviour of the estimate of a regression mod...
AbstractIn this short note, we derive an expression for the asymptotic covariance matrix of the univ...
The Partial Least Squares approach (PLS) is a multivariate technique which was originated around 197...
Abstract Partial least squares (PLS) was first introduced by Wold in the mid 1960's as a heuris...
Let (X, B, Y) denote a random vector such that B and Y are real-valued, and X ∈ R2. Local linear est...
Let (X, B, Y) denote a random vector such that B and Y are real-valued, and X ∈ R2. Local linear est...
A vital extension to partial least squares (PLS) path modeling is introduced: consistency. While mai...
A vital extension to partial least squares (PLS) path modeling is introduced: consistency. While mai...
Partial Least Squares Regression (PLS-R) method is regression linear technique for multivariate pred...
PLS regression methods have been used in applied fields for two decades. Techniques based on iterati...
High-dimensional datasets with a large number of explanatory variables are increasingly important in...
This paper derives the limiting distributions of least squares averaging estimators for linear regre...