The object of these short notes is to give a set of convenient symbols to define the sample space for the different compositional vectors that can be arranged into a three-way array. For the exploratory analysis of three-way data, Parafac/Candecomp and Tucker3 are some of the most applied models for low-rank decomposition of three-way arrays. Here, in addition to the relative geometry, is presented a concise overview as to how the elements of a three-way array can be transformed into compositional form and the relative geometry is given
Three-way Tucker analysis and CANDECOMP/PARAFAC are popular methods for the analysis of three-way da...
For the exploratory analysis of three-way data, Parafac/Candecomp model (CP) is one of the most app...
AbstractTucker three-way PCA and Candecomp/Parafac are two well-known methods of generalizing princi...
The object of these short notes is to give a set of convenient symbols to define the sample space fo...
The object of these short notes is to give a set of convenient symbols to define the sample space fo...
For the exploratory analysis of three-way data, the Tucker3 is one of the most applied models to stu...
The R package ThreeWay is presented and its main features are illustrated. The aim of ThreeWay is to...
For the exploratory analysis of three-way data, e.g., measurements of a number of objects, on a num...
For the exploratory analysis of three-way data, the Tucker3 is one of the most applied models to stu...
For the exploratory analysis of three-way data, e.g., measurements of a number of objects, on a num...
Matrices can be diagonalized by singular vectors or, when they are symmetric, by eigenvectors. Pairs...
In Chapter 1 we presented several denitions and concepts whose comprehension was crucial to fully un...
The Tucker3 model is one of the most widely used tools for factorial analysis of three-way data arra...
The Tucker3 model is one of the most widely used tools for factorial analysis of three-way data arra...
Compositional data (CoDa, [1] and [2]) consist of vectors of positive values summing to a unit, or i...
Three-way Tucker analysis and CANDECOMP/PARAFAC are popular methods for the analysis of three-way da...
For the exploratory analysis of three-way data, Parafac/Candecomp model (CP) is one of the most app...
AbstractTucker three-way PCA and Candecomp/Parafac are two well-known methods of generalizing princi...
The object of these short notes is to give a set of convenient symbols to define the sample space fo...
The object of these short notes is to give a set of convenient symbols to define the sample space fo...
For the exploratory analysis of three-way data, the Tucker3 is one of the most applied models to stu...
The R package ThreeWay is presented and its main features are illustrated. The aim of ThreeWay is to...
For the exploratory analysis of three-way data, e.g., measurements of a number of objects, on a num...
For the exploratory analysis of three-way data, the Tucker3 is one of the most applied models to stu...
For the exploratory analysis of three-way data, e.g., measurements of a number of objects, on a num...
Matrices can be diagonalized by singular vectors or, when they are symmetric, by eigenvectors. Pairs...
In Chapter 1 we presented several denitions and concepts whose comprehension was crucial to fully un...
The Tucker3 model is one of the most widely used tools for factorial analysis of three-way data arra...
The Tucker3 model is one of the most widely used tools for factorial analysis of three-way data arra...
Compositional data (CoDa, [1] and [2]) consist of vectors of positive values summing to a unit, or i...
Three-way Tucker analysis and CANDECOMP/PARAFAC are popular methods for the analysis of three-way da...
For the exploratory analysis of three-way data, Parafac/Candecomp model (CP) is one of the most app...
AbstractTucker three-way PCA and Candecomp/Parafac are two well-known methods of generalizing princi...