search for: sigular

...ances among the data. Assume the data matrix X is zero-meaned, and I used the following procedures: C = covriance(X) %% calculate the covariance matrix; [EVector,EValues]=eig(C) %% L = diag(EValues) %%L is a column vector with eigenvalues as the elements percent = L(1)/sum(L); Others argue using Sigular Value Decomposition(SVD) to calculate the same quantity, as: [U,S,V]=svd(X); L = diag(S); L = L.^2; percent = L(1)/sum(L); So which way is the correct method to calculate the percentage explained by the first principal component? Thanks for your advices on this. Fred

...writing to seek any help on "lme" error message. I am using lme to do Mixed-model linear regression. I use my simulated data. However, sometimes, I get the following error message, which I do not understand. "Error in solve.default(pdMatrix(a, fact=TRUE)): system is computationally sigular" I would appreciate any help about it. Thanks a lot Jingyuan Fu Drs, Groningen Bioinformatics Center the Netherlands [[alternative HTML version deleted]]

Hi, I run a maanova analysis and found this message error: Error in ma.svd(X, 0, 0) : 0 extent dimensions I did a google search and found this: \item ma.svd: function to compute the sigular-value decomposition of a rectangular matrix by using LAPACK routines DEGSVD AND ZGESVD. \item fdr: function to calculate the adjusted P values for FDR control. I did a search for LAPACK and not found a package. Could you help me on how I could solve this problem? I am try to do this: l...

...del using: fit<-coxph(Surv(start, end, status)~cov); When I fit the model to my data set (Which has 89 observations and 81 distinct time points, sort of large.), I always got a message that "Process R segmentation fault (core dumped)". Would you let me know if it is due to the matrix sigularity in the computation of the partial likelihood or something else? And how should I fit a cox model with external time-dependent covariates? Thanks a lot for your time and help! Sincerely, Rui Song ______________________________________________ R-help at stat.math.ethz.ch mailing list https://st...

...a from the all the partitions, this is the key for # the parallelism technique, I don't know how to do this step if # I was somehow doing QR decomposition. A = P1_A + P2_A # ... + P3_A ... + PN_A b = P1_b + P2_b # ... + P3_b ... + PN_b # calculate regression, this fails because of sigularity solve(A) %*% b # If I exclude the introduced column it works, but I'm not # sure how this would be generalized. solve(A[-5,-5]) %*% b[-5] # Compare to lm() lm(Murder~UrbanPop+Assault+Rape+Introduced, P)