Linked Questions

12 votes
2 answers
10k views

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
2k views

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
227 views

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
28 views

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
31k views

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
2k views

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
8k views

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
3k views

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
6k views

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
4k views

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
3k views

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
266 views

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
665 views

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
784 views

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
147 views

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

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