Linked Questions

12 votes
2 answers

Multivariable vs multivariate regression [duplicate]

I am a little unsure about the semantics in this regard, and was hoping someone could cast some light on this. As far as I understand, multivariable is basically one dependent variable and several ...
Denver Dang's user avatar
  • 1,047
7 votes
1 answer

What is the difference between multiple regression & mutivariate regression? [duplicate]

I have data on GDP growth as a dependent variable and growth in main production sectors of Pakistan such as mining, electricity, communication, manufacturing and electricity. I am supposed to run a ...
maryiam's user avatar
  • 71
2 votes
0 answers

Multivariate Regression? [duplicate]

All I know about multivariate regression is that there's multiple outputs. I'd like to learn more, but I have no idea where to start because all of the tutorials that say 'multivariate regression' ...
user avatar
0 votes
0 answers

How to predict single y target based on several X values? [duplicate]

I try to predict the result of an personality type test based on how people answered. My sample consists of the answers which range from 1 (strongly disagree) to 7 (strongly agree). Six answers lead ...
yemy's user avatar
  • 129
51 votes
5 answers

Why do we need multivariate regression (as opposed to a bunch of univariate regressions)?

I just browsed through this wonderful book: Applied multivariate statistical analysis by Johnson and Wichern. The irony is, I am still not able to understand the motivation for using multivariate (...
KarthikS's user avatar
  • 1,176
24 votes
6 answers

Advanced regression modeling examples

I'm looking for an advanced linear regression case study illustrating the steps required to model complex, multiple non-linear relationships using GLM or OLS. It is surprisingly difficult to find ...
Robert Kubrick's user avatar
8 votes
2 answers

Simple, multiple, univariate, bivariate, multivariate - terminology

I do realise (some of) this has already been addressed here (e.g., Why do we need multivariate regression (as opposed to a bunch of univariate regressions)?, Explain the difference between multiple ...
Tilen's user avatar
  • 820
4 votes
2 answers

How to handle dependent, multidimensional output in machine learning

I have some data where X is n x p and Y is n x d, where d = 36. To recreate it I am currently training 36 independent models to take X and recreate Y one column at a time. It works okay, but it ...
Pavel Komarov's user avatar
7 votes
1 answer

Readdressing the semantics of multivariate and multivariable analysis

There was a post once upon time dealing with the differences of multivariable and multivariate regression. I have seen the relevant post here. However I am having this debate with a colleague and ...
user4673's user avatar
  • 1,661
2 votes
1 answer

Normal equation for multivariate linear regression

What is the normal equation for multivariate linear regression? In the case of monovariate linear regression, using ordinary least squares, to obtain $\theta^* = \text{argmin}_{\theta} \sum_{i=1}^m (\...
Franck Dernoncourt's user avatar
3 votes
2 answers

Multivariate regression vs. multiple univariate regression models

This is a naive question, but I am a little confused over the term "multivariate" regression. And note this question does not (to my knowledge) pertain to "multiple" regression. When people use the ...
24n8's user avatar
  • 1,147
3 votes
2 answers

A fundamental question about multivariate regression

This is slightly embarrassing, as I've done a fair amount of statistical work, but for years I've heard this niggling voice at the back of my head, and I need to ask someone. I remember when I first ...
James's user avatar
  • 473
2 votes
2 answers

Multivariate Solutions to Nonlinear Data

I've been surveying the different methods of approaching linear multivariate problems (ex PCA, PLS, factor analysis etc.) and want generate a model for Y's that depend non-linearly on $X$'s via ...
Francisco C's user avatar
2 votes
1 answer

Logistic Regression models with two or more response variables in R/SAS

There are a lot of inconsistencies in the literature over what should be the appropriate term(s) for the regression models involving two or more responses, and if they are binary/continuous, for more ...
AAA's user avatar
  • 123
2 votes
0 answers

Prediction with multiple Outputs

i try to find an algorithm that meets my expectations. Following Scenario: I want to predict the delivery of natural ressources (ores). So i have data with composition of the ressources from a ...
TheJed's user avatar
  • 21

15 30 50 per page