Questions tagged [multivariate-regression]
Regression with more than one response (dependent) variable.
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SEs in multivariate regression
To avoid confusion, my question refers to multivariate regression as multiple dependent variables for the same set of independent variables.
As far as I understand (see e.g., this question), the ...
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0answers
23 views
Multivariate Linear Regressions with heterogeneous covariance matrices
Let $\mathbf Y$ be $N\times K$ response matrix and $\mathbf X$ be $N\times (p+1)$ design matrix (including the intercept), consider the multivariate linear regression,
$$
\mathbf Y = \mathbf{XB+E}\,,
$...
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0answers
30 views
How to compute sobol indices from a multi-variate regression model?
I have a dataset that consists of 300 input variables, 200 response variables, and 15000 samples. These response variables are basically a profile of 200 different values of the same response and they ...
1
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1answer
39 views
Corrections for logistic regression (multiple comparisons?)
I'll cut to the chase. Here's what I'm doing:
looking at the influence of water temperature and salinity on the presence of water-borne parasites for a certain estuarine bird population
birds are ...
0
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2answers
25 views
Test for comparing corresponding coefficients in multivariate regression
This question is related to this but I am hoping for more tangible techniques than a general discussion.
For simplicity, suppose I am trying to linearly model two correlated responses $Y_1$ and $Y_2$ ...
1
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1answer
18 views
p-value of multivariate response in partykit::ctree
I wonder if anyone can help me to understand the two questions regarding partykit::ctree:
what's the difference between "quadratic" and "maximum&...
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0answers
17 views
mcglm matrix linear predictor - Error in base::tcrossprod(x, y) : non-conformable arguments
I'm trying to fit a multivariate multiple regression model using the mcglm package (version 0.6.0) and have faced problems when specifying components of the matrix ...
2
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1answer
59 views
Model selection for multivariate mixed models
I would like to perform a multivariate mixed model but am a bit confused about model selection for such models. I wonder if I could get some help here.
When fitting a univariate mixed model, to avoid ...
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0answers
97 views
Including both binary and Gaussian responses in one multivariate mixed model in MCMCglmm
I would like to fit a multivariate mixed model to a dataset that contains: a binary Direction variable showing the direction the individuals moved toward, a continuous PropRangeChange_s variable ...
0
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1answer
50 views
When will lasso and regression tree perform differently?
If I want to use lasso and regression tree respectively to generate the important variable lists. I'm wondering when will they generate lists with a huge difference? Under what signal structure?
4
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2answers
154 views
How do I make sense of 200 regression models?
I'm dealing with a dataset that has about 300 input features, and about 200 response variables and consists of 25000 samples. These response variables are basically a profile of 200 different values ...
2
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0answers
31 views
Difference between several univariate regressions and one multivariate regression in a machine learning context
I know there are several other questions asking for the advantages of multivariate regression over several univariate regressions (e.g. this). I understand that the dependent variables can be ...
0
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1answer
52 views
How does SPSS calculate composite variable for MANOVA/Multivariate multiple regression?
I have analysed my data using multivariate multiple regression (8 IVs, 3 DVs), and significant composite results have been found.
Before reporting my findings, I want to discuss in my results chapter ...
0
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1answer
117 views
Setting priors for bivariate regression
I would like to perform a bivariate MCMC regression with boldness scores as the continuous response variable, aggression ranks as the ordinal response variable, trial numbers as fixed effect and ...
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0answers
41 views
Multivariate regression with a mix of ordinal and continuous dependent variables [closed]
I would like to run a multivariate mixed regression MCMC model with two response (independent) variables, namely x and y. x is continuous while y is ordinal. There is one predictor variable that is ...
0
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1answer
29 views
Is multivariate regression the right test?
Data
Amount spent on product type A
Amount spent on product type B
5 age groups
External factor X
External factor y
I have data in the form of monthly sums over 60 months for all of those data-...
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0answers
24 views
How to calculate the ratio of observations to model parameters in a VAR(p) model
In machine learning, it's pretty common to use the general rule of thumb that one should have at least 10X as many observations as there are model parameters to avoid overfitting.
As discussed here ...
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0answers
14 views
Liklihood ratio test and linear mixed effects regression
I have a data set which includes sex, age, and 5 polygenic scores as independent variables, with 16 dependent variables. I have constructed univariate linear mixed effects regression models and ...
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0answers
10 views
Comparing two approaches to modeling dependence in bi-variate Gaussian regression
Presume we would like to model the dynamics of two related variables as a bi-variate Normal, while also accounting for the effect of other covariates (via regression).
E.g. I would like to model ...
1
vote
1answer
70 views
Forecasting a time series $(x_t,{\bf Y_t})$ where all we care about is forecasting $x_t$
Consider a multivariate time series $(x_t,{\bf Y}_t)$ $1\le t \le n$ taking values in $\mathbb{R}^{d+1}$, and suppose that we wish to forecast $x_t$ using its own path as well as the "exogenous" ...
0
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1answer
28 views
Best way to find correlation between categorical response variables and continuous explanatory variables
Sorry if this is a really simple question, but I'm very new to multivariable statistics and I'm trying to find a best method to deal with my ecological dataset.
I recorded the environmental ...
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0answers
23 views
How can the cost function dimensionality be understood?
Most tutorials on the internet demonstrate the cost function with the m * x + b = y function,
which is fine and understandable for a start..
They presents the ...
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0answers
27 views
How to interpret the hinge function for multivariate adaptive regression splinesļ¼
I do not understand why we need a reflected pair (t-x)+ for MARS.
Could you please interpret more about the hinge function?
0
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1answer
28 views
Does multivariate regression produce the same results as multiple, single regressions? [duplicate]
I've read a variety of answers on this topic and as far as I can see, the consensus is that multivariate regression is different from multiple, individual linear regressions. I also understand that in ...
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0answers
17 views
in r, comparing two regression models with same number of independent variables for significant difference in prediction
I have two models that have the same dependent variable. Each model has 3 independent variables and differ on 1 of those variables (a continuous variable). I am not trying to select for which model ...
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0answers
30 views
What does multivariate regression get us that several univariate regressions do not? [duplicate]
("Multivariate" regression in this post means a multidimensional response variable.)
I have been playing with multivariate regression for the past two days, and I have noticed something that did not ...
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0answers
90 views
Geometric interpretation of the difference between the means (ANOVA)
First of all, a disclosure: I'm a medical doctor trying to understand statistics for research. Coming from a non-mathematical background I can do many mistakes. I've read some traditional books of ...
4
votes
1answer
160 views
Confidence interval for covariance in multivariate linear regression
Let $X\in R^{n\times q}$ and $Y\in R^{n\times p}$ be our data matrices, and we assume that they are related by a linear model $Y = BX + \Xi$, where $B$ is fixed and unknown and each row $\Xi_i \sim \...
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0answers
54 views
How do we know adding an uncorrelated variable to a regression will not change existing coefficients?
Say I have a regression with 3 independent variables and I decide to introduce a 4th variable and rerun the regression.
A previous post states that the coefficient on an original variable will change ...
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0answers
24 views
Is single-output regression the same as univariate?
Similarly, is multi-output regression the same as multivariate regression?
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0answers
21 views
Whither multivariate regression?
I've been handed someone else's data (again). It's measurements of six proteins' levels from 20 human brain samples, 5 each of different stages of a disorder. I'd like to run a multivariate regression,...
0
votes
1answer
43 views
What to do with statistically insignificant dummy/categorical variables? [duplicate]
From the research I've done the common answer is that you can not remove insignificant dummy variables from a regression. I'm having a hard time finding academic papers or books that back up this ...
2
votes
1answer
85 views
Correlation in the residuals of a multivariate linear regression
I'm using a multivariate multiple linear regression model to predict 4 scalars out of multiple regressors. I'm not sure if this model is a good one and now I'm trying to asses the validity of the ...
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0answers
112 views
Multivariate zero_one_inflated_beta regression
I want to run a zero_one_inflated_beta regression with brms on the following multivariate formula:
...
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0answers
21 views
Regression when each observation of the dependent variable is a vector [duplicate]
The OLS formation $Y = \beta X$ and its derivation all have dependent variable $Y$ as a $n$ by $1$ vector, each entry of $Y$ is a scalar observation. But what if each observation is a vector of size $...
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0answers
18 views
when to give up in fitting a variable? [duplicate]
I would like to predict a variable from 5 features.
I have bad scores (<50%) with all the algorithm I tried (Random Forest, Lasso, SGD, MLP).
I would like to quantitatively assess if I should ...
1
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0answers
36 views
RStan v.s. simple lm for multivariate regression [closed]
I want to fit a multivariate linear regression, with $Y_1, \dots,Y_4$ as the response and $X_1,\dots,X_n$ as the explanatory variables. $X_1$ and $X_2$ are two components of a mixture, and $X_3,\dots ,...
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0answers
89 views
Mathematics behind single input, multiple output regression
I have sought some help and trained a regression model that takes in a single dependent variable Y and gives the three independent variable R, B and G as output. This has been done in attempt to ...
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0answers
27 views
Simultaneous equation model with endogenous regressors
Let's assume four dependent variables $Y_1$, $Y_2$ and $Y_3$ that are correlated. I want to evaluate the impact of several regressors: $X_1$, $X_2$ and $X_3$ on these 3 dependent variables using a ...
0
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0answers
31 views
How to get change of basis matrix for Canonical Correlation Analysis?
A bit of background: I am trying to create toy example of the Curds and Whey regression shrinkage algorithm in python. In a standard multivariate regression this algorithm uses canonical correlation ...
2
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0answers
44 views
Estimating conditional probability distribution from samples
I have three continuous variables, $X$, $Y_1$ and $Y_2$. All three are correlated. For a given value of $X$, the conditional probability distributions of $Y_1$ and $Y_2$ are typically bimodal. I'm ...
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0answers
52 views
Formulas for multivariate meta-regression
everyone!
I'm digging in meta-regression and doing hand calculations using WLS to get better understanding of the topic. I'm fine with calculations for univariative model (that is, 1 covariate is ...
1
vote
1answer
47 views
How can I determine the overall Cox proportional hazard HR in multivariate analysis?
I am using the survival and survminer packages in R. I use the data and code below as an example. See also the output below. I ...
2
votes
2answers
813 views
Anyone know Multivariate OLS on Statsmodels? [closed]
I trying to run a mutivariate multiple regression using Statsmodels. Not sure if this is the best tool for this type of regression, so please do tell me if there's another package to which I should ...
1
vote
2answers
62 views
Regression with multiple dependent variables controlling for age and gender [closed]
I have multiple dependent variables (interval) and one independent variable (interval). I would also like to control for age (interval) and sex (categorical). Is this possible in SPSS?
Moreover, my ...
2
votes
1answer
150 views
Adjustment for multiple comparison in bayesian multivariate regression model (using brms)
I am investigating age and timepoint effects on different (correlated) EEG parameters in a repeated measurements structure. I chose to use the brms R package to fit a bayesian multivariate model with ...
0
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0answers
19 views
Simulate multivariate outliers
Considering a multivariate linear model $\boldsymbol{Y = XB + E}$, where $\boldsymbol{Y, X, B}$ and $\boldsymbol{E}$ have dimension $n \times m$, $n \times p$, $p \times m$ and $n \times m$, ...
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0answers
25 views
Comparing the performance of multivariate with univariate linear regression model
Let $\boldsymbol{Y} = \boldsymbol{X\beta} + \boldsymbol{E}$ a multivariate linear model, where $Y \in \mathbb{R}^n \times \mathbb{R}^m$ a dependent variable, $\boldsymbol{X} \in \mathbb{R}^n \times \...
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0answers
26 views
Parameter estimation in bivariate linear models
I'd like to simulate data from a bivariate normal distribution to a regression problem. In other words, let $X = (X_1, X_2)$, where $X_1$ and $X_2$ be two matrices $n \times 1$. $X_1\sim N(3, 2)$ and $...
0
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1answer
124 views
Linear regression with stochastic gradient descent p-values
Is there any way to get summary statistics (p-value specifically) for the results of a multivariate linear regression ($y = X\beta + \epsilon)$ using gradient descent? Most online library ...
