# Questions tagged [multivariate-regression]

Regression with more than one response (dependent) variable.

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### Multivariate analysis. Hypothesis income variable increases 2 outcome variables simultaneously

I am working on an epidemic analysis on a known blood disease. My outcome variables are two, lets call them A and B. I have already two income variables lets call them c and d, that have been proved ...
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### Time series Prediction as a multi-output multivariate regression for many input and output values for each lag [closed]

Recently I am working on time series prediction. My topic is related to wind turbine blades which has many sections in each blade. Now we want to predict some performance and metrics of 51 sections of ...
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### Is it okay to use Multivariate Multiple Regression on correlated independent and dependent variables?

I'm confused on this one. So, I'd appreciate it if you could help me explain this a little bit. So, I have about 15 independent variables and 3 dependent variables. out of these 15 independent ...
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### How to construct a regression model with two inter-dependent dependent variables?

Let's work through a concrete (if somewhat impractical) example: I'm a medical researcher who has reason to investigate a possible trend in a dataset of tissue samples from the human lung and human ...
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### Comparability of multivariate vs multiple regression

I have 3 layers of data [in individual columns] indicating different characteristics of resistance of vegetation to stress across a city. I have another layer of median income for my study area. I ...
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### problem with linear regression

I made a linear regression multiple model, I've got all the parameters insignificant with high p value, I get this result: The variables are time series. Rates except Polity which is natural number ...
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### Detecting changes in multivariate time series

I have the following problem I am trying to solve. I am hoping to pick your brain on the possible solutions. I have (say) 10000 machines, each one spit out a number for me each day; I have collected ...
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### Are multivariate probit models with the same set of explanatory variables for each outcome more efficient that piecewise probit regressions?

I understand that multivariate probit models are analogous to SUR models. In the SUR case, there's no efficiency gain by fitting a SUR model over several independent OLS regressions when the model ...
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### Approaching a multivariate regression problem with multiple observations over days

Assume for every $Y_{n*1}$, there is a covariate matrix $X_{n*p}$. The goal is to predict $Y'_{n*1}$ when new $X'_{n*p}$ becomes available. What complicates the matter is that I have $k$, let's say ...
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### Why do we need adjustment when applying Ljung-Box test over residuals?

Why do we need adjustment when applying Ljung-Box test over residuals? The following is from the Multivariate Time Series Analysis by R. Tsay. ...
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### Can I try applying multiple linear regression when there is no correlation with independent variable

Can I still try multiple linear regression when there is no or very small(2 to 10%) correlation (Pearson) between the Independent variable(continuous) and Dependent variable(continuous). But very ...
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### comparing coefficients from multivariate regression

I have a multivariate linear regression model where the predictors are concentrations of different drugs, of the same units, and the responses are the survival percentages of each different kind of ...
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### Terminology for regression with more than 1 independent variable and more than 1 dependent variable?

I know that multiple regression corresponds to the case where we have 1 dependent variable and multiple independent variables. Multivariate regression, on the other hand, corresponds to the case where ...
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### GLM in Matrix Notation

I would like to verify my thoughts here concerning matrix notation of generalized linear models (i.e. generalized general linear models). A classical generalized linear model is given by  Y_i = h(\...
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### What's the point in neural networks for multivariate regression?

Do you have any case in which fitting a multivariate regression (so having multiple output nodes) outperforms the fitting of a single output one at a time in terms of accuracy? I ask this because ...
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### What's the difference between multivariate regression and univariate regression? [duplicate]

If we have $Y$ as response variable which has more than 1 component, and we do want to do regression, then is there such a thing as multivariate regression, and if so, how those it differ from ...
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### Summary of manyglm model objects running too slowly in R; can I speed them up?

I have implemented two independent multivariate abundance regressions, both of which use the manyglm function in the mvabund ...
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### A reasonable multivariate regression error metric

How would you compare error metrics of a multiple output regression? Normalised mean square error for each variable? How about for the overall performance of the model, would you just take the mean ...
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### 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 ...
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### Neural network for multiple output regression

I have a dataset containing 34 input columns and 8 output columns. One way to solve the problem is to take the 34 inputs and build individual regression model for each output column. I am wondering if ...
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### 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 (...
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### Can two multicollinear variables affect a third IV that is not correlated with the two?

I have three dependent variables, $X_1$ (my 'main' independent variable), $X_2$ $X_3$ where When I test $X_1$ against the response variable y in a bivariate regression, the results are not ...
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### Multivariate linear regression with lasso in r

I'm trying to create a reduced model to predict many dependent variables (DV) (~450) that are highly correlated. My independent variables (IV) are also numerous (~2000) and highly correlated. If I ...
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### Multivariate Regression equivalent to Multinomial Regression (aggregated variables)?

Context (optional) In genetics one often uses data coming from SNP (Single Nucleotide Polymorphismes) which are genetic markers of which several (usually 2) versions (a.ka. alleles) exists in a given ...
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### Choice of algorithm for fitting Multivariate Covariance Generalized Linear Models

I am using the mcglm function in R to fit a Multivariate Covariance Generalized Linear Model. Although the help for the ...
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### Clarification on multivariate regression

In (what I call) standard regression, we have a problem of the form $y=f(a,b,c,d)$. Is it correct to say that multivariate regression is the problem of the form $g(x,y,z)=f(a,b,c,d)$? In case this is ...
Can I apply generalised linear regression to a multiresponse setting? I mean the regression $Y = \beta X + \epsilon$ where $\beta$ is a parameter matrix and $Y$ is a response vector, in my case ...