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# Questions tagged [reduced-rank-regression]

Multivariate multiple linear regression with a constraint that the coefficient matrix should be of low rank.

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### Comparison/Visualisation of Regression Methods

This question follows this question, in particular @amoeba's clarifying answer and the plot from the SAS documentation included. I'm especially interested in knowing if $\mathbf{X}, \mathbf{Y}$ are ...
31 views

### Low Rank Gaussian Process vs Bayesian Linear Regression

A main benefit of Gaussian Process Regression is, that we not only get a prediction, but also a variance that we might use as indication of the prediction confidence. While bayesian linear regression ...
50 views

### I'd like to do regression using canonical correlation analysis

I got two multidimensional datasets, X and Y. I thought I build the model, which explains the relationship between two datasets, using canonical correlation analysis (CCA). The first correlation ...
32 views

234 views

### Reduced rank regression with binary outcome variable

I am trying to find dietary patterns related to a disease outcome. Unfortunately, I only have the binary outcome "disease yes/no" as outcome. I tried to perform PCA on the data, but the dietary ...
465 views

### Definition of “meta-parameter” [duplicate]

What is meant by the term "meta-parameter"? Can a definition, informal and/or formal, be provided? For example, in reduced-rank regression, the rank ($r$) can be referred to as a meta-parameter of ...
338 views

### Probabilistic models for partial least squares, reduced rank regression, and canonical correlation analysis?

This question results from the discussion following a previous question: What is the connection between partial least squares, reduced rank regression, and principal component regression? For ...
2k views

### What is the connection between partial least squares, reduced rank regression, and principal component regression?

Are reduced rank regression and principal component regression just special cases of partial least squares? This tutorial (Page 6, "Comparison of Objectives") states that when we do partial least ...
1k views

### Objective function of canonical correlation analysis (CCA)

Given two vectors of random variables $X$ and $Y$, Canonical Correlation Analysis (CCA) finds the transformation matrices $A$ and $B$ so that $\operatorname{corr}(A_{1*} X, B_{1*} Y)$ is first maximal,...
9k views

### What is “reduced-rank regression” all about?

I have been reading The Elements of Statistical Learning and I could not understand what Section 3.7 "Multiple outcome shrinkage and selection" is all about. It talks about RRR (reduced-rank ...
2k views

### Friendly tutorial or introduction to reduced-rank regression

I am trying to learn Reduced-Rank Regression (RRR) from The Elements of Statistical Learning. I find the writing and them mathematics a little too prohibitive. Does any of you have a resource/text/...