Extend the MatrixTerm type with a piv vector and rank integer scalar. Use a pivoted Cholesky factorization to determine the computational rank of X'X. fixef gains an additional, logical argument pivoted that defaults to true. coef always returns the fixed-effects coefficients in the original order. Coefficients for columns found to be linearly dependent are set to -0.0 so that X*coef(m) is the fitted value that would be obtained via projection. add the 1-argument methods for StatsBase.predict (the result is equivalent to StatsBase.fitted)
In this article, I describe an alternative approach for fitting linear models with multiple high-ord...
We present an algorithm for updating the symmetric factorization of a positive semi-definite matrix ...
Hierarchical functional data are widely seen in complex studies where sub-units are nested within un...
Add a method for αβAc_mul_B! needed when evaluating ranef on a model with nested, vector-valued rand...
AbstractIn reduced-rank regression, a matrix of expectations is modeled as a lower rank matrix. In f...
<div><p>Situations often arise in which the matrix of independent variables is not of full column ra...
We consider linear mixed models in which the observations are grouped. A `1-penalization on the fixe...
Situations often arise in which the matrix of independent variables is not of full column rank. That...
International audienceLinear mixed models are especially useful when observations are grouped. In a ...
Situations often arise in which the matrix of independent variables is not of full column rank. That...
This paper proposes a new method to estimate the rank of the beta matrix in a factor model. We consi...
This thesis which consists of four papers is concerned with estimation methods in factor analysis an...
An approach for the analysis and inference of unbalanced mixed models is presented. Given a mixed mo...
The consequences of factoring alternative correlation matrices are investigated assuming ordinal sca...
International audienceMany applications of machine learning involve the analysis of large data frame...
In this article, I describe an alternative approach for fitting linear models with multiple high-ord...
We present an algorithm for updating the symmetric factorization of a positive semi-definite matrix ...
Hierarchical functional data are widely seen in complex studies where sub-units are nested within un...
Add a method for αβAc_mul_B! needed when evaluating ranef on a model with nested, vector-valued rand...
AbstractIn reduced-rank regression, a matrix of expectations is modeled as a lower rank matrix. In f...
<div><p>Situations often arise in which the matrix of independent variables is not of full column ra...
We consider linear mixed models in which the observations are grouped. A `1-penalization on the fixe...
Situations often arise in which the matrix of independent variables is not of full column rank. That...
International audienceLinear mixed models are especially useful when observations are grouped. In a ...
Situations often arise in which the matrix of independent variables is not of full column rank. That...
This paper proposes a new method to estimate the rank of the beta matrix in a factor model. We consi...
This thesis which consists of four papers is concerned with estimation methods in factor analysis an...
An approach for the analysis and inference of unbalanced mixed models is presented. Given a mixed mo...
The consequences of factoring alternative correlation matrices are investigated assuming ordinal sca...
International audienceMany applications of machine learning involve the analysis of large data frame...
In this article, I describe an alternative approach for fitting linear models with multiple high-ord...
We present an algorithm for updating the symmetric factorization of a positive semi-definite matrix ...
Hierarchical functional data are widely seen in complex studies where sub-units are nested within un...