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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12 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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18 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
9 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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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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13 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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7 views

Sample for Algorithm Implementation [on hold]

How can a 10 * 10 matrix, with 10 columns co-related with each other with some statistical functions and 10 rows as a time-series instances be sampled as a single instance ? I would like to plot N ...
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25 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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4 views

mvregress matlab — weights [on hold]

I have a multivariate linear regression problem. There are 3 responses. Slopes and intercepts are independent. There is only one explanatory variable. I can fit the model just fine. The issue I'm ...
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30 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
12 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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24 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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2 views

variance covariance matrix of with Autoregressive structer [closed]

I have multivariate data U distributed MN(0,sigma^2AR(1,rho)) I want to find the mle of the sigma and rho
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21 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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7 views

Multi-target regression Datasets

I'm looking for a dataset for multi-target regression . I found severals but these datasets have few instances since I need datasets with more 100k instances. Anyone knows where I can find it besides ...
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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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6 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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15 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. ...
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1answer
35 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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12 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 ...
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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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56 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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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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6 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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32 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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18 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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11 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 ...
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29 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 ...
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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 ...
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29 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 ...
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11 views

How do I find what the population for a survey looked like?

I have a large dataset on a population and the results of a survey conducted on individuals from some other population (don't know the relation between the two populations, there's probably some ...
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8 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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12 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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11 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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32 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 ...
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18 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 ...
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20 views

Inclusion of exogenous variables and prediction of TVAR models (tsDyn package in R)

I'm trying to use the function TVAR from tsDyn package in R, but I'm having problems in including exogenous variables. Also, I still haven't found a way to predict ...
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15 views

Estimating time-varying factor loadings with MGARCH - R

I have a model of returns Yt = Bt.Xt with 4 independent variables and I am trying to estimate the time-varying factor loadings. If Y & Xs are defined as GARCH models, is it possible to estimated ...
2
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1answer
43 views

Looking for proper method to analyse a data sample (n=200) with a huge amount of variables (800)

I have a data sample (approx 200) from a population of about 60 000 people. There are around 800 columns/variables in my data (the reason being that I had a few questions for which I applied a ...
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1answer
165 views

Do I need to use multivariate regression or several regression analyses?

I have a data set of 45 participants with 96 variables each (although some measurements are missing). Some variables are simple such as age and disability while other measurements are scores on some ...
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16 views

Filtering before multivariate analysis

I am a newbie in statistics and this may be a silly question. For a n << p problem, I wonder if it is feasible to first filter variables according to some criterion, for example correlation ...
3
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0answers
27 views

Outlier removal for univariate and multivariate analysis

I have a biological data set on which I would like to do both univariate and multivariate analysis, and try to find correlation of features to a response. Should I remove univariate outliers and do ...
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18 views

Trend break down using statistical models

I have a time series data with revenue for each week. Following are the independent variable information available for each week- margin,number of customers,units sold per customer. There is a ...
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24 views

Visualizing 3-D fit

I have two independent variables, call them X and Y, and I have to fit a dependent variable Z = f(X,Y) somehow. In an experiment, the experimentalist measured Z as a function of X, and another ...
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4answers
246 views

What are variable importance rankings useful for?

I have become somewhat of a nihilist when it comes to variable importance rankings (in the context of multivariate models of all kinds). Often in the course of my work, I am asked to either assist ...
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0answers
15 views

Transformations possible when performing a single multivariate ANOVA on a continuous and categorical species database?

I want to study the impact of aquaculture on a hard rocky seafloor community which is naturally low in diversity. 4 replicate images (0.25 m2 each) were taken at fixed distances (0, 20, 40, 80, 120, ...
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10 views

Multi-response Multivariate Coefficient of Determinations

For the linear model, $$ \bf{Y} = \mu_{Y} + \bf{B}^t \left(\bf{X}-\bf{\mu_X}\right) + \boldsymbol{\epsilon} $$ Where, $\bf{Y}$ is a $n \times q$ matrix of $q$ responses, and $\bf{X}$ is a $n \times ...
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1answer
21 views

What should be the ratio between number of cases and attributes in multivariate regression?

Is there any way to determine if it is feasible to perform a multivariate regression based on a given number of samples and attributes? For example I have a data set with 6 cases , 30 attributes and ...
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0answers
16 views

Gibbs Sampling for Multivariate Case

I understand the procedure for Gibbs sampling for bivariate case but I got confused about Gibbs sampler for multivariate normal distribution. I guess I should try to determine the conditional ...
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8 views

Setting bounds on multivariate data sets with possible multiple distribution types

Summary: I've got data sets whose distribution seems to differ based on where on the x-axis the data occurs. Using some common distribution mean and std dev calculations do not produce acceptable ...