Analyses where there is more than one response or dependent variable of interest. This can be contrasted with "multiple" or "multivariable" analysis, which typically implies more than one predictor or independent variable.

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19 views

Restricted Maximum Likelihood (REML) Estimate of Variance Component

Let, $$\mathbf y_i = \mathbf X_i\mathbf\beta + \mathbf Z_i\mathbf b_i+ \mathbf\epsilon_i,$$ where $\mathbf y_i\sim N(\mathbf X_i\mathbf\beta, \Sigma_i=\sigma^2\mathbf I_{n_i}+\mathbf Z_i \mathbf ...
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2answers
15 views

How to normalize and compare growth rates between variables at different stages of some kind of growth model “curve”?

I have a data frame that has various capital and metropolitan cities with various economic, market and performance data. One set of variables is each total annual non-domestic visitor volume and the ...
3
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1answer
66 views

Meta-regression with highly-correlated predictors? Should I do 2 analyses? Example in R

I'm trying to do meta-regression with a lot of trials (>40 trials with >100 'arms') investigating the efficacy of a procedure (abl) and any 'addon' procedure. Each trial will have 2 or more arms. In ...
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0answers
8 views

Implementation of Meila's VI criterion in Python? [on hold]

I am doing some clustering experiments and came across this paper by Marina Meilă in the Journal of Multivar Statistics, where she presents a very interesting metric for evaluating clusterings called ...
2
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1answer
13 views

How the total pseudo R2 is calculated with the “dissmfac” function in TraMineR?

I am using the discrepancy analysis in TraMineR. I performed univariate analysis with "dissassoc" to measure the effect of each variable. Then, I did a multi-factors analysis using "dissmfac" to ...
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10 views

How to deal with different distribution families in multivariate regression?

Say that I have 2 dependent variables, one continuous and one count: amount of adrenaline (continuous) number of remembered digits in a task (count) and I want to check if these two variables ...
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26 views

How to describe my problem when my features are vectors?

My problem is a multivariate time series of measurements from a chemical sensor. There are $n$ different experiments made with as many different substances. Each experiment ranges over $t$ time steps. ...
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46 views

identification condition in factor model

Consider the following factor structure: $\Sigma=\Lambda \Lambda' + \Phi$ where $\Sigma$ is $p \times p$, $\Lambda$ is $p \times m$ without any restrictions and $\Phi$ is a $p \times p$ diagonal ...
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9 views

what is the difference of prediction model in high dimensional setting and multivariate setting?

I am wondering what is the difference of prediction model in high dimensional setting and multivariate setting. Do the difference just lie in that we need to make dimension reduction for high ...
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0answers
21 views

How do I analyze “Analysis of deviance” in R?

I ran an ANOVA in R in the library (mvabund) which resulted in an output table "Analysis of Deviance", and I am confused as to what the "DEV" means in the output below. I am including here part of the ...
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4 views

Assumption of normal distribution in MANOVA/MANCOVA having determined various var lag structures

I am currently running a multivariate regression (MANCOVA) using macroeconomic factors and exchange rates. To fulfill the assumption of uni-/multivariate normality, I transformed all variables ...
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1answer
18 views

How to Combine Univariate GARCH Models?

We fitted univariate GARCH models to several time series. We would like to make sure that the forecasts also consider the correlation structure between the time series. The literature presents some ...
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19 views

Non parametric multivariate analysis

I need some help with my statistical analysis. I have two different pharmacokinetic parameters. They result from two different models applied on the same data. These data are baseline and follow up ...
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0answers
15 views

R - Pearson correlation in assessing multivariate regression performances

How to assess the performance of the multivariate regression outputs in different scenarios using Pearson's correlation in R ? Is it a straight process to compare the correlation of expected values ...
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2answers
74 views

What's in a name: Precision (inverse of variance)

Intuitively, the mean is just the average of observations. The variance is how much these observations vary from the mean. I would like to know why the inverse of the variance is known as the ...
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4 views

Difference of means in 3 dimensions (Hotelling's T^2 for 3 dimensions or equivalent)

I am trying to determine if two groups are different in 3 dimensions (3 variables). I am looking for something similar to Hotelling's T^2, but for 3D instead of 2. I have two groups 'Known Color' and ...
2
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14 views

Mahalanobis distance for highly multivariate random variable

I have to compute the Mahalanobis distance for a $10^6$ dimensional multivariate random variable. What is the best (and fastest) way to do this? I am currently taking cholesky decomposition of the ...
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1answer
14 views

Co-variate contribution to model accuracy in multi-variate analysis

I have implemented a multivariate analysis in R as such: lm1<-lm(Y ~ A + B + C + D + E, data=data, weights = 1/Uncert) I found that the variable A contributes ...
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1answer
38 views

Finding outliers in multiple dimensions

I'm working on dataset which isn't normally distributed. It contains three dimensions: cost, discount and profit. I'm trying to find outliers in all these dimensions. I used $\text{z-score}$ to find ...
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0answers
28 views

Optimal block length for block bootstrap with multivariate time series

I've got a multivariate time series $\mathbf{X}_t$, where $t$ is time and there are $p>1$ columns of $\mathbf{X}_t$. There is autocorrelation in the data. I'm interested in various functions of ...
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1answer
13 views

DCC-GARCH: selection of error distribution and extraction of volatility decay

I am in a hesitation of detecting which indicators from maximum likelihood (ML) estimates of the Gaussian DCC model tell the volatility parameters' decaying. Another question is, how to know which ...
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0answers
14 views

Method to determine whether or not users had a bad experience based on multiple variables: Average Bandwidth, Latency, and frame rate

I would like a recommendation on the best statistical method to use, as well as any suggested R packages to achieve this goal. I have three variables, Bandwidth, Latency, and frame rate for a set of ...
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0answers
14 views

checking the expectation of the maximum likelihood estimator $\mathbf{\Sigma}$ for the multivariate gaussian

I am trying to find the expectation of the MLE for $\mathbf{\Sigma}$ for the multivariate gaussian. $E(\mathbf{\Sigma}_{ML}) = E\left (\dfrac{1}{N} \sum (\mathbf{x}_n - \mathbf{\mu})(\mathbf{x}_n - ...
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0answers
40 views

Covariance matrix of multivariate multiple regression coefficients

I would like to perform a regression analysis on a dataset comprising one independent variable (X) and two dependent variables (Y1 and Y2) which may be affected by correlated errors. R's stats::lm ...
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0answers
31 views

show asymtotic normality

Let $x=(x_1,x_2,...,x_n)$ be a sample from a multivariate normal distribution, with mean vector $\mathbf{\mu}$ (n by 1 column vector, all elements equal to $\mu$) and covariance matrix $\Sigma$ ...
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1answer
17 views

Models for nonnegative (incl. zero) positively skewed multivariate time series (trade volumes)

I want to build a Monte Carlo simulation that is based in part on share amounts that are traded in the market for a set of stocks. I need to be able to take into account the co-dependence of trade ...
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0answers
31 views

maximum likelihood for multivariate gaussian (covariance estimator)

Given the multivariate gaussian $N(\mathbf{\mu}, \mathbf{\Sigma})$, I want to get the maximum likelihood estimator for $\mathbf{\Sigma}$. I start with the log likelihood function $\ln p(\mathbf{X}) ...
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0answers
25 views

Fitting a multinomial regression with multiple dependent variables and random factors (R)

I have a dataset with multiple dependent variables, which are counts of about 53 different categories of debris found on beaches. I also have a variety of independent variables, some of which I am ...
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12 views

Multi-target regression Datasets [closed]

I'm looking for a dataset for multi-target regression . I found severals but these datasets have few instances and I need datasets with more than 100k instances. Does anyone know where I can find ...
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0answers
5 views

Tukey HSD for multuple variables and single variable giving different results [duplicate]

I have tried to run Tukey HSD for multi-variable dataset. However, when I run the same test on a single variable, the results are completely opposite. To be more specific: code: ...
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0answers
7 views

Online Semi-supervised Multi-target regressor

I'm searching for a online semi-supervised multi-target regression algorithm. The only algorithms that I can find work all in batch mode. Is there anybody to suggest one... Is there anybody who have ...
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0answers
18 views

How to choose right method for comparing multiple variables.

I need help with choosing method. I am on my first experiment with plants. I will be watching plants at three different types of medium. Each medium will be in different temperature conditions. ...
3
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1answer
39 views

Variance of a multivariate AR(1) process

I have a multivariate AR(1) process (first-order vector autoregression, VAR(1)) of the form $$ \pmb X_{t+1} = A \pmb X_t + \zeta_t $$ where $\pmb X_t$ is a vector, $A$ is a matrix and $\zeta_t \sim ...
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0answers
13 views

How to perform a multivariate-regression on all ordinal variables

I'm trying to do some analysis on the effect of the economy on voting behavior for my undergraduate dissertation. I am relatively new to statistics and trying to get to grips with it, but currently ...
0
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0answers
23 views

diagnostics for PLSR?

I am trying to apply sPLS2 type pf regression my matrix y has a set of clinical variables and matrix X has some gene data .I am using mixOmics package in R. My question is how to decide that my ...
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0answers
65 views

Predicting multivariate uneven time series of discrete/categorical data

I have a basic background in stats, DSP, ML etc. but by no means an expert so some of my terminology is going to be rusty. It probably makes the most sense if I simply show you what i wanted to do and ...
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0answers
49 views

Identification in confirmatory factor analysis

Consider a factor analysis $x_{ik} = a_{i} f_k + u_{ik}$. Usually, this model is estimated with identification restriction, say, with the first component of $f_t$ being one. This is to address the ...
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0answers
13 views

Multivariate tests vs. mixed repeated measures ANOVA

I am hoping some one can help clarify my ambiguity in my analysis. My study has a pre/post design, meaning there are 4 groups in my study (1 control and 3 experimental groups ). the participants ...
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0answers
42 views

Classification of multivariate time series datasets

I have data where each feature is a multivariate time series dataset with a known class label. Each feature is of dimension 4xn and contains per-second measurements of 4 different variables A, B, C ...
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33 views

SPSS vs R: test of flatness in profile analysis

I'm trying to do a profile analysis on a relatively simple design, but I'm getting different numbers between R and SPSS for specifically the test of flatness My data looks like this: ...
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0answers
20 views

Shouldn't results from glm function (fitting the model) agree with anova() function which uses the fitted model for chi-square test?

I have tried to organize the results so that you can easily understand what I am trying to ask. Please look at the background and results below my questions. I will appreciate if I can get answer to ...
2
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0answers
30 views

Easiest way to prove that Hotelling $T^2$ follows $F$ distribution

Suppose that $x_i \overset{iid}{\sim}N_p(\mu,\Sigma), (i=1,...,n)$. Define $$T^2=n(\bar{x}-\mu)'S^{-1}(\bar{x}-\mu)$$ where $\bar{x}=n^{-1}\sum_{i=1}^nx_i$ and ...
0
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0answers
10 views

Multiple correspondece analysis

Ploting the two-dimensional map using multiple correspondece analysis, one gets specific words in one of the four quadrants. Is it important the location of words in a specific quadrant, or can one ...
0
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0answers
31 views

Is there a good equivalent of multivariate normal distribution for strictly positive data?

More precisely: the distribution of data for each variate is similar to gamma/exponential distribution; and there are strong inter-variate correlations which I would like to take into account. A ...
0
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0answers
11 views

Unequal levels of independent variable in regression with non-randomized groups

I'm running a multivariate regression (multiple continuous DVs) that also has multiple predictors (1 two-level categorical, 1 continuous). The categorical predictor is the group participants were in, ...
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0answers
13 views

Unconditioinal covariance of factors in go-GARCH

In this pdf in section 2.4 page 11 Alexios Ghalanos explains the theory behind the go-GARCH model (general orthogonal GARCH). I don't understand why the unconditional covariance is $$\operatorname{E} ...
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18 views

Examples (and how to generate them) of various conceptually different datasets to throw at PCA to gain better intuition for it [duplicate]

I've developed a solid understanding of principal component analysis to the point where I can actually write my own implementation of it in python. I fear this is the easy part where the hard part is ...
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0answers
14 views

Calculating the eigenvectors of a covariance matrix when there are fewer samples than coordinates

Appendix B of this paper gives the proof to extract the eigenvectors of a covariance matrix using a 'smaller' covariance matrix. My question is, does the eigenvectors obtained through the method ...
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33 views

Why are principal components of the residuals from a multivariate regression correlated with the estimated coefficients?

Say I have some data that follows a general linear model: $$ Y = XB + E $$ for which: $Y \in \Re^{n \times m}$, $X \in \Re^{n \times p}$ and $B \in \Re^{p \times m}$ Further, let's assume (1) that ...
1
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0answers
26 views

Threshold for Mahalanobis distance

I have training samples that I project onto the eigenspace via pca. What is a reasonable threshold for the mahalanobis distance (to the mean) to reject invalid input data ? The paper here states that ...