Regression with more than one response (dependent) variable.

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Hidden markov model multivariate regression with time-series data

I am working with a dataset that includes the trajectories of various car trips and would like to be able to predict their destinations using only a subset of the trip trajectory. For instance, if in ...
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5 views

How to use SPSS to compare the regression weights of each predictor for different outcomes variables In multivariate regression,

In my example, I have three outcome variables and two predictors, so I need to use multivariate regression to do the analysis. For the first step, I tested the predictors are significant for the ...
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1answer
23 views

Multivariate Linear Regression with continuous and discrete explanatory variable

I have some trouble to apply a multivariate linear regression on my data. I have two features gross_area which is continuous, nb_bathrooms which is discrete (1,2,3) and a dependent variable y which is ...
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1answer
54 views

What does 'Controlling for' mean in regression? [duplicate]

I am working towards completing my undergrad honours thesis and I am in the process of analyzing and writing up my discussion section that is dealing with some form of multiple regression (can't ...
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16 views

Confusion over MANOVA and Regression for my research study

I have a research study that I am planning but I am a little confused as to what kind of analysis I should be doing. On that one hand, I thought MANOVA. On the other, some other people think it is a ...
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32 views

Finding a Multiple Response Linear Regression Data Set

I'm looking for a dataset where one can apply multiple response linear regression. Ideally, this dataset would have a large number of responses and predictors relative to the sample size, and both ...
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81 views

Collinearity in multivariate regression with huge amounts of data

Take the following example. I wish to predict physical performance as a function of height and weight. I already know weight negatively affects performance. Height also negatively affects performance, ...
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43 views

Multiple Versus Multivariate Regression

I have 4 IVs and 4 DVs and not sure if I have to use linear regression (one IV and one DV at a time) or multiple regression (the 4 IVs and one DV at a time)? Is there any application where I can put ...
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20 views

Getting a confidence interval for a predicted value in regression

So I have this table of statistics which I'll try to reproduce below. It is meant to be a summary of a multivariate regression of "PolityIVScore" against log foreign aid and a dummy variable for ...
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38 views

Is there such thing as regression involving a pairwise response variable? (X,Y)~Z0+Z1*B1

I'm trying to model a pairwise outcome of basketball game scores. Ie. (94,87),(102,98),(76,54),... My input variable is a single performance metric for each team. Ie. (12,9),(14,17),... Is there a ...
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1answer
560 views

How to do MANCOVA in R?

I have two groups of persons, GRP0 and GRP1, on which I measured three continuous variables: VAR1, VAR2 and VAR3. I would like to use Mancova in R with: - VAR1, VAR2 and VAR3 as outcome variables - ...
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56 views

Pairwise comparison of slopes from multivariate regression model in R

I am investigating size changes over time. I have five size variables in a multivariate linear model against year. I used the Anova() function in the car package to test whether the slopes are equal ...
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30 views

Sparse PLS: algorithm for variable selection and model fitting

In the spls package in R (based on the manuscript by Chun and KeleĊŸ [1]), there is a separate specification for the variable selection and fitting in the main function, ...
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31 views

RANSAC Multivariate Regression

I am using RANSAC as my robust regression method. I saw many examples for a line and a plane but what if there are many independent variables as in multivariate regression. Is there anyway handle ...
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17 views

Multiple binary dependent variables

I want to model multiple binary outcomes with some predictors. Does MANOVA can handle this or is there any other techniques I can use? Thanks !!!
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41 views

Multivariate regression with 3 dependent variables and only 1 independent variable?

I need to compare the marginal effect of one independent variable (X) in 3 different dependent variables (Y). I did a multivariate regression using Stata commands manova and mvreg, but I am doubting ...
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76 views

Bivariate Zero-inflated negative binomial distribution regression?

I have two correlated random variables, for one experiment, the readout look like: For random variable A: ...
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1answer
60 views

Curse of dimensionality mimics multicollinearity?

Why does the curse of dimensionality mimic multicollinearity, in the following sense.. Consider the random vector $Y = [y_{1}, \dots, y_{4}]$ where each element is ~ Uniform (0,1). Take 10 samples ...
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52 views

Compare $R^2$ statistical significance in multivariate multiple regression

I have a multivariate multiple regression model with 3 dependent variables and the same 5 covariates. I used manova and mvreg in ...
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185 views

Many dependent variables, few samples: is this an example of “large $p$, small $n$” problem?

"Large $p$, small $n$" typically refers to "many independent variables, few samples". In my case, I have $1$ independent variable, $300$ dependent variables, and $n < 20$ samples. Thus, my case ...
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33 views

Covariance for a multivariate Bayesian Additive Regression Tree

Chipman, George, and McCullogh (2010) state that: One can also extend the sum-of-trees model to a multivariate framework such as: $$ (29) \qquad\qquad Y_i = h_i\left( x_i \right) + ...
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1answer
88 views

Multiple regression or multivariate regression

Are there any difference in beta coefficients when doing several multiple regression analysis as compared to doing multivariate regression?
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What are some suggestions for analysis of and model development for a small sample of data?

I originally planned on path analysis utilizing multivariate multiple regression to test my hypothetical model - but I am not getting my sample size. I have looked at non-parametric regression ...
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1answer
204 views

Multivariate Linear Regression in Python

How to compute the overall standard error of a linear regression model using Python? Which library should I use? I am looking for something like this, however, I can't see how to get the overall ...
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1answer
196 views

Which regression analysis should I use for ranked dependent variables and proportional independent variables?

I am analysing the effect of deprivation on breastfeeding and am wondering which type of regression analysis I should use. It is area level data. Deprivation data is available as a score from 0 - ...
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References suggested for multivariate analysis of several similar time series

I have a time series dataset that reports the hourly page views and social media shares of online news stories. What I hope to obtain is the relationship between the two variables. I would imagine ...
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Using a PCA to reduce response variables or multivariate multiple regression?

Does it make sense to use a PCA (principal component analysis) on a set of response Y variables and then conduct a multiple regression, or carry out a multivariate multiple regression all response ...
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123 views

How to do multivariate regression in R?

I need to preform a multivariate normal regression in R. The question is: Let $Y_1$, $Y_2$, and $Y_3$ follows multivariate normal distribution. What is the conditional of $Y_3$ given ...
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2k views

Lag order for Granger Causality Test

Suppose I'm considering several independent variables for possible inclusion in an ARIMAX model I'm developing. Before fitting different variables, I'd like to screen out variables that exhibit ...
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30 views

What are some multivariate models with feature interactions

I have dependent variable matrix $Y_{i,j}$ and feature matrix $X_{i,k}$. My objective is to predict each element of the vector $[y_{i,0},...,y_{i,J}]$ by using new observations of the features, ...
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29 views

Covariance matrix specification in multivariate probit

Im having trouble with a multivariate probit model with partial observability/sample selection (written in GAUSS). In this model there is a probit at each of multiple stages, and only one of the two ...
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16 views

Marginally Uncorrelated Responses in Multivariate Regression

Consider the multivariate regression with random predictors as described in Izenman's Modern Multivariate Statistical Techniques, that is, $X : r \times 1$ and $Y: s \times 1$ are jointly normally ...
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58 views

Regression by multiple dependent variables with constraints & feature selection

I have a data set of 1000 records. Each record has three dependent variables $y_1, y_2, y_3$ and 100 independent variables $x_1,...,x_{100}$, where the dependent variable $y_i$ satisfies: $0\le y_i ...
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125 views

Alternative to MANOVA when group covariance matrices are heterogeneous?

I'm running into problems meeting some of the assumptions of MANOVA, namely homogeneous group covariance matrices and normality. I'm looking for an alternative approach where assumptions are not ...
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76 views

Parameter covariance matrix for a multivariate (matrix-Y) logit model

I've got a partially-observed unidirectional network. Nodes can be linked (0/1) in one of many ways. For now, lets call them $y_1$ and $y_2$. The unit of analysis is the potential network link ...
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300 views

Formula to calculate beta matrix in multivariate analysis [duplicate]

I have to implement a multivariate analysis on $n$ random variables with a sample of $m$ data points. I would like to get a matrix with the $\beta$ (as in $n$ $\beta$ vectors put together). Is ...
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2answers
2k views

Multivariate regression with weighted least squares in python?

I have a multivariate regression problem that I need to solve using the weighted least squares method. In particular, I have a dataset X which is a 2D array. It ...
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403 views

What is the difference between multiple regression & mutivariate regression?

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 ...
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56 views

$R^2$ in multivariate regression

I'm trying to determine how the population $R^2$ value is defined in the multivariate regression model where we have $Y_i = \mu_y + B^\prime(X_i - \mu_x) + err$ Where $Y_i \in \mathbb{R}^q$ and ...
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130 views

What type of multivariate linear regression is this?

I'm trying to reproduce a result from a book (see bottom) and it doesn't work. I would like to do some further readings about this method but he doesn't specifically give the method other than a ...
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54 views

Self study problem: Predicting performance using multivariate linear regression

I'm trying to improve my statistics knowledge using football(soccer) results. So, this is a self study problem. You don't have to provide a complete solution. Pointing me in the right direction is ...
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32 views

Controlling for respondents' propensity to rate high/low or moderate/extreme

I am doing a simple linear regression to test the relationship between voters' self-reported policy stands and their approval ratings for two hypothetical presidential candidates in a simulated ...
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67 views

causal inference with correlated multivariate outcomes

I've been struggling with how to think about the causal estimate of a program on two outcomes, when one of the two outcomes affects the other outcome. It seems sort of like simultaneous equations, ...
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292 views

Fitting a multilevel multivariate model in R with `glmer`

Background I have a large dataset that contains three binary outcomes for individuals belonging to groups. I am interested in jointly modeling these binary outcomes because I have reason to believe ...
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1answer
490 views

Finding the best linear model for each response variable in multivariate multiple regression using R

I don't know if a similar problem has been asked before so if it has been, please provide me a link to the related/duplicate questions. I am sorry if I seem to be asking too much. But I really like to ...
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177 views

Prediction Intervals for General Linear Model

How do I derive prediction intervals for a general linear model? My general linear model written in matrix form is, $$ \mathbf{Y} = \mathbf{X} \mathbf{B} + \mathbf{R}$$ with each of the rows of ...
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45 views

Modeling consumer demand for a multi-tiered product that is subject to cannibalization?

I'm looking for research/white papers on demand estimation for goods/services that are offered on a tiered-basis with varying prices (i.e. more complex the good/service, higher the price.) I'm not ...
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535 views

Casting a multivariate linear model as a multiple regression

Is recasting a multivariate linear regression model as a multiple linear regression entirely equivalent? I'm not referring to simply running $t$ separate regressions. I have read this in a few ...
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174 views

Coupling time series information from sources with multiple spatial resolutions/scales

I have many satellite raster images available from different sensors. From these, the coarser ones have a very abundant temporal resolution. The medium resolution rasters tend to have less acquisition ...
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how to explain the anova object for a multivariate linear regression?

I performed a multivariate linear regression such that: fit<-lm(as.matrix(y)~mwtkg+mbmi+mage,data=x) where $y$ is a $500 \times 26$ multivariate outcomes. ...