# Probabilistic partial least squares model: Identifiability, estimation and application

@article{Bouhaddani2018ProbabilisticPL, title={Probabilistic partial least squares model: Identifiability, estimation and application}, author={Said el Bouhaddani and Hae-Won Uh and Caroline Hayward and Geurt Jongbloed and Jeanine J. Houwing-Duistermaat}, journal={J. Multivar. Anal.}, year={2018}, volume={167}, pages={331-346} }

## 10 Citations

### On some limitations of probabilistic models for dimension‐reduction: Illustration in the case of probabilistic formulations of partial least squares

- MathematicsStatistica Neerlandica
- 2022

Partial least squares (PLS) refer to a class of dimension‐reduction techniques aiming at the identification of two sets of components with maximal covariance, to model the relationship between two…

### On some limitations of probabilistic models for dimension-reduction: illustration in the case of one particular probabilistic formulation of PLS.

- Mathematics
- 2020

Partial Least Squares (PLS) refer to a class of dimension-reduction techniques aiming at the identification of two sets of components with maximal covariance, in order to model the relationship…

### Statistical integration of heterogeneous omics data: Probabilistic two‐way partial least squares (PO2PLS)

- Computer ScienceJournal of the Royal Statistical Society: Series C (Applied Statistics)
- 2022

A global test for the relationship between two datasets is proposed, specifically addressing the high dimensionality, and its asymptotic distribution is derived.

### Statistical Integration of Heterogeneous Data with PO2PLS

- Computer Science
- 2021

A general framework, probabilistic two-way partial least squares (PO2PLS), which models the relationship between two datasets using joint and data-speciﬁc latent variables and performs better than alternatives in feature selection and prediction performance.

### Statistical integration of two omics datasets using GO2PLS

- Computer SciencebioRxiv
- 2020

GO2PLS integrates two omics datasets to help understand the underlying system that involves both omics levels and incorporates external group information and performs group selection, resulting in a small subset of features that best explain the relationship between two omic datasets for better interpretability.

### Statistical Integration of Multiple Omics Datasets Using GO2PLS

- Computer Science
- 2020

The simulation study showed that introducing sparsity improved the performance concerning feature selection, and incorporating group structures increased the precision and power of the feature selection procedure.

### Joint Modeling of An Outcome Variable and Integrated Omic Datasets Using GLM-PO2PLS

- Computer Science
- 2022

This article extends dimension reduction methods which model the joint part of omics to a novel method that jointly models an outcome variable with omics and shows that the model provides more insight by jointly considering methylation and glycomics.

### Monitoring of Industrial Processes via Non-stationary Probabilistic Slow Feature Analysis Machine Learning Algorithm

- Computer Science
- 2020

The proposed NS-PSFA algorithm has better performance in non-stationary applications such as a continuous stirred tank reactor (CSTR) and a three-phase flow industrial process in comparison with the CVA and PCA methods.

### Statistical method for modeling sequencing data from different technologies in longitudinal studies with application to Huntington disease

- BiologyBiometrical journal. Biometrische Zeitschrift
- 2020

For one out of 14 genes, the initial significant result could be replicated with both technologies using data from both time points, but statistical efficiency is lost due to disagreement between the two technologies, measurement error when predicting gene expressions, and the need to include additional parameters to account for possible differences.

### Mapping Particle Size and Soil Organic Matter in Tropical Soil Based on Hyperspectral Imaging and Non-Imaging Sensors

- Environmental Science, Computer ScienceRemote. Sens.
- 2021

This study successfully generated, from the imaging sensor, a large-scale and detailed predicted soil maps for particle size and SOM, which are important in the management of tropical soils.

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