Tagged Questions

0
votes
1answer
51 views

What happens to the covariance matrix when the errors are independent?

I was wondering, what happens to the covariance matrix of the errors, when I assume that all the errors are stochastically independent? Is the covariance matrix still: $$\sigma^2I = ...
0
votes
2answers
74 views

Covariance matrix explanation

I try to understand and visualize myself covariance matrix. Supposing I have a matrix A = [ 2 3 4; 5 5 6 ], how do I calculate its covariance matrix, and what is ...
0
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0answers
217 views

Variance Covariance matrix of regression coefficients

In a procedure, I am resampling (bootstrapping) from a Y vector and X matrix. For each resample, I standardize. Then I run a linear model, and obtain the regression coefficients for each variable of ...
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0answers
26 views

Why are the eigenvalues of a covariance matrix corresponding to the data's variance? [duplicate]

For multi-dimensional data, we can compute its covariance matrix, and then the eigenvalues and eigenvectors. It turns out that the eigenvector with the largest eigenvalue corresonds to the direction ...
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0answers
84 views

Singular covariance matrix and Spatially-correlated random effects [closed]

I'm interested in incorporating spatially-correlated random effects into my model to explicitly account for between-observation spatial autocorrelation, such that spatial autocorrelation decreases ...
2
votes
0answers
187 views

Problem when creating matrix of values based on covariance matrix

I want to simulate a data set with similar covariance structure as my observed data (which is a SNP by gene p-value matrix, dim ~600k*8368), and have calculated a covariance matrix (dimensions ...
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0answers
160 views

Covariance matrix in R with non-numeric variables

I am modeling a Gaussian distribution for a computational biology application, and I am working in the statistical package "R". In this regard, my problem is that I have to construct a covariance ...
0
votes
1answer
773 views

Problem with singular covariance matrices when doing gaussian process regression

I'm working with gaussian process regression. Currently I start testing differnt covariance functions and compositions to see what type of data they could describe best. I made an own implementation ...
0
votes
1answer
298 views

Does transpose commute through expectation?

Working with the generalized covariance formula for vector, $x$, I have: $E[(x-\mu)(x-\mu)^T)] = E(xx^t) - \mu E(x^T)$ But the term $E(x^T)$ doesn't make much sense to me. Does anyone have an idea ...
3
votes
1answer
124 views

Efficient parametrization of the covariance matrix with some covariances constrained to zero

I'm trying to estimate the unknown 8x8 covariance matrix X in R using the maximum likehood, but I have problems of figuring out the efficient way of parametrization of X when some of the covariances ...