Questions tagged [multivariate-analysis]
Analyses where there is more than one variable analyzed together at once, and these variables are either dependent (response) ones or the only ones in the analysis. This can be contrasted with "multiple" or "multivariable" analysis, which implies more than one predictor (independent) variable.
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R package for order selection of a vector ARIMA(p,d,q) for multivariate time series
I'm currently working on a project that requires dealing with multivariate time series. What I would like to fit to my dataset is a VARIMA(p,d,q) . I'd like to proceed using the Box-Jenkins procedure, ...
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If Y is the sum of normalized multivariate pareto random variables then Y is a Feller-Pareto random variable
If we let $\underset{k\times 1}{\boldsymbol{X}}=(X_1, \dots, X_k)' \sim MP^{(k)}(\boldsymbol{0},\boldsymbol{1}, \alpha)$ where MP denotes a Multivariate-Pareto distribution, with joint survival ...
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Structural or sensitivity analysis of multivariate time series with multiple subjects
Sorry if this isn't explained in the best way. I have very basic knowledge of time series analysis so my question may sound very simplistic or might be missing the big picture of this type of analysis....
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Time series data with seasonality using model VAR and VARMA [duplicate]
I have a time series with seasonal economic data, and other time series to see if this variable help predict my time series, but the VAR model is not a model for seasonality.
What options do I have ...
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How to determine how much variation was due to the differences between a group?
I am working on the data set that consists of Patients (after stroke), Time (then can walk after a going through the program), and Program they follow.
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Choosing response and predictors
Information on the Girth (), Height () and Volume () for 31 cherry trees
yielded the following correlations : $r_{12}$ = 0.519, $r_{23}$= 0.598 and $r_{13}$= 0.967. If you were asked to setup a ...
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Hidden Markov Model - Baum Welch algorithm initialization
Currently I'm working on a problem where I have a multidimensional, continuous sequence of observations $X$ that model my response variable $y$ with two states $0$ and $1$. I assume that this sequence ...
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Should I apply PCA on every sample of a multivariate time series dataset and calculate mean values or should I reshape the 3D array into 2D?
I am relatively new to PCA and can't find a sufficient answer to my question. I have got a multivariate timeseries dataset of the shape [1200 (Samples), 100 (Timesteps), 18 (Variables)].
I want to ...
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ADONIS post-hoc tests?
I wondered how I should figure out which groups and which variables caused significant differences in the adonis test.
I have multiple carbon isotope variables from organic compounds and different ...
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Multivariate multilevel ordinal regression
I am looking to estimate a multivariate multilevel ordinal regression model (preferably via the ordered logit) in $R$ using non-bayesian methods. Is anyone aware of a package that does this? If not, I ...
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Should the N events that is output by coxph when using counting process format be the same as the N events prior to reformating?
I am performing a coxph analysis using time dependent and time independent covariates.
I have formatted my data into the counting process form to allow for time dependent covariate.
Prior to changing ...
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Generating multivariate random variable with normal and exponential marginals
I have a collection of data points of the form $[U, V, X, Y]$, where $U$ ~ $N(\mu_1, \sigma_1)$; $V$ ~ $N(\mu_2, \sigma_2)$; $X$ ~ $exp(\lambda_1)$; and $Y$ ~ $exp(\lambda_2)$, and I am looking to ...
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Multiplying (or averaging) effect of independent Bayes Factors
I want to know how to combine the effect of Bayes Factors calculated on subsets of a dataset. Note, this is not the case of replication BF, where I have, say a BF from a previous study (which acts ...
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Find the principal component and the proportion of the total population variance explained by each when the variance covariance matrix is given
I can understand the part where we have to find the principal component from the variane covariance matrix- find eigen values, make eigen vector and normalise. The principal component would be ...
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The p value of my OPLS-DA model was -nan(ind), I don't know, what's mean, and the residual MS was infinite, I need help here?
I obtained for the first time strange cross-validation results of my OPLS-DA model, the CV ANOVA was -nan(ind), SD residual was inf, MS residual was inf also, moreover, F test equal to zero.
The ...
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What kind of information can be extracted from a similarity matrix?
Say, you have an N×N similarity matrix. What kind of information can you extract from a similarity matrix and what is its intuitive meaning? For instance, one could compute trace (meaningless), ...
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Is Chi square appropriate to show one set of binary data comes from a different population than another set of binary data?
I am comparing the accuracy of different computer programs on making predictions on the same set of data inputs. For example each of 5 computer programs read in the same 100 data points, and make a ...
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Can autocorrelation impact joint probability?
This is probably a pretty stupid question... but assume I have two random variables, X1 and X2. I want to look at their dependency (joint probability) at some quantile q. Theoretically, in the ...
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What test to use to control for socio-economic status (MANOVA?)
Newbie question. I'm studying the stress levels of a minority population and I intend to compare it with the stress levels of a majority population. However, I'd like to explore whether discrimination ...
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Confidence Intervals for More than One Variable?
Consider the univariate case, suppose we have some sample data on the heights of men and women - we are interested in estimating the average heights of men and women in the population, and the ...
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How to structure multiple linear regression model given dependent variables with multiple timepoints?
I'm working with a dataset that has multiple independent variables (e.g. height, sex, zip code, etc.) as well as dependent variables with multiple timepoints (i.e. test A results reported at 1wk, 2wk ...
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How to split the data into multiple (normal) distributions or clusters?
I am trying to train a machine learning model to predict yield on fields, based on multiple parameters, such as elevation, humidity, and nitrogen content. Observing the historical harvest data, I ...
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How to handle regressions with outliers in panel data
I have collected panel data for some countries. I am running several regressions, from simple OLS to IV to panel data methods combined with IV etc.
Unfortunately, I see in R that some observations are ...
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Conditional exponential family implies joint exponential family
Suppose $p(X_j | X_1,\ldots,X_{j-1})$ comes from some known exponential family for every $j=1,\ldots,k$. Does it follow that the joint distribution comes from some (possibly different) exponential ...
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How to test the significance of contribution of a variable in Factor analysis and what is the resonable rule for removing a variable from FA?
My question is about the credibility from the statistical point of view of what I have seen in some papers where the researchers (non-statistician) define some kind of staged factor analysis (FA) and ...
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Cluster analysis of time series data with a few points in time
I have asked the question here before but have not been able to resolve it.
I have data from 150 participants who were asked about their emotional state at 3 points in time. There are 28 different ...
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t-Copula Simulations of Bivariate Random Variables: Assigned Correlation != Calculated Linear Correlation
I have an n x n correlation matrix of random variables. Consider the following example:
What I would like to do is study the behavior of the joint distributions using a t-Copula with, say, 5 degrees ...
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In multiple regression, How to find the range of independent parameter for which regression equation is applicable/valid?
I have generated a multiple-regression equation/model from the data.
Parameter A in the data varies from $0.1$ - $10$.
Parameter B in the data varies from $100$ - $1800$.
Parameter C in the data ...
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Discarding highly correlated variables
I have got a dataset of $N$ observations with $k$ predictors $x_1, ..., x_k$ and a vector $y$ of binary responses, where $y \in \{0,1\}$.
I assume that given a class my data comes from a $k-$...
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Overlap coefficient for two multidimensional normal distributions
For two PDFs $f_1(x)$ and $f_2(x)$ the overlap coefficient (OVL) measures the similarity between two distributions through the overlapping area of their distribution functions and is given by the ...
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Calculating the change in target wrt a change in a specific feature
I have a feature set $X=[x_1,x_2,...x_n]$ including numerical and categorical variables with high cardinality, and a target variable $y$.
I am interested in how $y$ would change if a particular ...
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Multiple correlated multivariate time series
I have forecast dataset containing multiple multivariate time series that are not independent from each other. A state in one of the the series in time "t" can influence the state in another ...
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How to analyze the relationship between two continuous variables beyond regression and EDA?
I have two continuous variables (net_profit and duration_of_operation) and I want to examine relationships between these. So far, I've done regression analysis, hierarchical clustering, correlation ...
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Urban Site observation data analysis suggestion
I have conducted site observation at four different locations for a period of 20 mins. (Total of 30 observations for each site). During the site observation, the pedestrian counts, age group and ...
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Multi Input Multi Output (MIMO) for time series forecasting
I'm dealing with a problem where I have several different sources of multivariate time series, and these sources have an interaction, in a way that the dynamics of the overall system is affected by ...
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Could nomogram be built with odds ratio or beta-coefficients only in R?
I have a retrospective chart review that reported beta coefficients for both its univariate and multivariate regression analysis. However, there is no complete individual patient data. I am wondering ...
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Assess whether distance from competitor affects sales in stores
Suppose I'd like to investigate whether proximity of a competitor store affects sales in my stores.
I'm struggling on how to frame the question from a regression perspective. Furthermore, there may be ...
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Estimating volatility of 15 stock market indices: univariate vs. multivariate models
I am working with R and with financial series of 15 stock market indices with a weekly frequency.
I want to obtain the estimated volatility since it is the input I need to perform a volatility ...
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GAMs with multiple time series predictors
I have a binomial classification (yes/no) made on about 100 words. For each word, I can compute several time series (fo, intensity, etc.). I’m finding difficult to model (using GAMs) the outcome, ...
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Normalization of coordinate in panel data? (timeseries)
I'm working with the neural networks and motion prediction on mesh data.
Objective of neural network is to predict $T_p$ frames in the future, given previuos $T_s$ frames. We have let's say 10 objects....
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Joint Exceedance Probability for Multivariate Distribution
I was reading this paper:
https://nhess.copernicus.org/preprints/nhess-2020-28/nhess-2020-28.pdf
Where the notion of "joint exceedance probability" is discussed for the bivariate case. That ...
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Question on appropriate solution to issue with IV in data (is the test still suitable?)
I have some pre-existing data, which was collected by my predecessors. For the data I typically would conduct a Multivariate General Linear Model. In this data I am collecting information about ...
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Removing/separating impact of variable on time series data
I have a time series with a trend and seasonality. What I would like to achieve is remove impact of variable X on Y, to learn how Y would look like if there were no impact of X.
Y is internal metric, ...
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Multivariate transfer entropy
I have a set of time series to treat as sources and a time series to treat as destination. From the definition of multivariate transfer entropy, it seems to me that it can only be defined on two ...
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How to adjust p-value for both multi-level and multi-variate comparison?
I have a naive statistical question:
Do I need to adjust p-values two times when I perform a multi-level and multi-variate comparison?
Suppose I have a data frame df...
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How to test both main effects and interactions using continuous variables?
My design has three continuous variables (duration 1-3), one ordinal variable (level), age and gender as independent variables. Dependent variables are six different questionnaire results.
I want to ...
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Univariate after stepwise regression?
My aim is to understand and describe the effect that independent variables (ordered and unordered factors and continuous) have on a continuous dependent variable.
First, I thought about using a ...
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multivariate classification r
I am analyzing a dataset with 5 factors(Y1,Y2,Y3,Y4,Y5).
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What's the appropriate encoding for logistic regression model between two sub-groups in a disease cohort (with no non-disease controls)?
I have a cohort of heart disease patients with a variety of diagnoses (n=300) that I'm analyzing. I want to run a logistic regression model on two sub-types of the heart disease (subtype A has n=50 ...
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Multiview CCA with one source set and multiple independent target sets
I have 5 datasets from the same subjects that can be interpreted as different data modalities for these subjects. 4 of these datasets describe brain-related data and the last one contains behavioral ...
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