Regression with more than one response (dependent) variable.

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MARS Model Validation

Can anyone please explain how to validate MARS Model in R. I am running MARS Model with categorical DV and IDV's. And also please explain how to validate the outcome results. Thanks
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Modelling against “day” or “day^2” in to look at change over time?

I'm a masters student trying to model changes in behaviour, heart rate variation and faecal cortisol as welfare measures in sheep over the course of 22 days. Days -4 to -1 is used as baseline, day 0 ...
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Instrumental variable regression related question

In Lubik and Schorfheide (2007), they are saying that The monetary policy rule can be represented as $$ R_{t}=X_{t}'M\beta_{1} + Y_{2}'\beta_{2}+\epsilon_{t}^{R} \hspace{1cm}(1) $$ where ...
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30 views

How to compare explained variances of nested multivariate multiple regression models?

I have two groups of continuous* variables - let's call them MF (5 variables) and OR (2 variables), plus some demographics. It has been previously found that the MF are associated with one of the OR ...
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43 views

Solution for Autocorrelation in Linear Regression Model - Economic Data

I am trying to estimate a multivariate linear regression model in the form of: $Y(t) = c + b_1*X_1(t) + b_2*X_2(t) + b_3*X_3(t) + b_4*X_4(t)$ All my variables (both Xs and Y) are Year on Year ...
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47 views

Errors-in-variables multivariate polynomial regression (R)

(EDIT: the question has been modified just a little bit to be more specific) I want to fit a multivariate polynomial regression that accounts for measurement errors (an Error-in-Variables model). ...
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multivariate student-t regression

(1) I want to do a multivariate regression in R (where each output sample is a vector, instead of a number), which I know can be handled using the lm() function; however, the multivariate output data ...
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248 views

Examples of Non-Linear Time Series?

Does anyone have an example of real world (ideally multivariate) time-series data that depends on its past in a non-linear, but additive way? I understand that there are several examples of ...
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107 views

Various methods for predicting multiple dependent variables (python)

I would like to model and predict multiple dependent variables depending on one or more independent variables. The most straightforward method appears to be multivariate regression. I was wondering ...
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1answer
61 views

Can regression be used with 3 observations and more than 3 independent variables?

I want to regress v1 on o1:o7. I would like to do the same for each of v2:v5 with ...
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22 views

books for introduction to statistics. [duplicate]

Good Morning, I am currently working with a process automation company. I am new in this field and wants to know more about statistics. If somebody can suggest some basic books on statistics where I ...
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66 views

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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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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28 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
107 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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22 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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60 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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114 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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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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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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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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1k 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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81 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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49 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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39 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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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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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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92 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
95 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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63 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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228 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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38 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
99 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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285 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
270 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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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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3k 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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37 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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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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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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369 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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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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64 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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140 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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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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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 ...