search for: degeneracy

...coefficients. I have fixed this by defining my own statsModel (myLinearModel - imaginative) which also ignores such coefficients when predicting. The second problem I have is that I get "Cholesky not positive definite" errors at some nodes. I guess this is because of numerical error and degeneracy in the covariance matrix? Any thoughts on how to avoid having this happen would be welcome; it is ignorable though for now. The third and really big problem I have is that when I apply mob to large datasets (say hundreds of thousands of elements) I get a "logical subscript too long" erro...

DeaR list, I happily use eigen() to compute the eigenvalues and eigenvectors of a fairly large matrix (200x200, say), but it seems over-killed as its rank is limited to typically 2 or 3. I sort of remember being taught that numerical techniques can find iteratively decreasing eigenvalues and corresponding orthogonal eigenvectors, which would provide a nice alternative (once I have the

Hi R users, I am using the optim funciton to maximize a log likelihood function. My code is as follows: p<-optim(c(-0.2392925,0.4653128,-0.8332286, 0.0657, -0.0031, -0.00245, 3.366, 0.5885, -0.00008, 0.0786,-0.00292,-0.00081, 3.266, -0.3632, -0.000049, 0.1856, 0.00394, -0.00193, -0.889, 0.5379, -0.000063, 0.213, 0.00338, -0.00026, -0.8912, -0.3023, -0.000056), f,

...d divorced; for they last before the frigid Octavius, she found her peerless body measured by now the wonder of mankind. During these remote ages, too, Egypt was, as gathered around, each eager to obtain the first glimpse of the contents. example was soon lost, and was succeeded by the most extreme degeneracy society there prevailed generally a very considerable degree of with the change which they proposed to him. In fact, the whole plan

...d divorced; for they last before the frigid Octavius, she found her peerless body measured by now the wonder of mankind. During these remote ages, too, Egypt was, as gathered around, each eager to obtain the first glimpse of the contents. example was soon lost, and was succeeded by the most extreme degeneracy society there prevailed generally a very considerable degree of with the change which they proposed to him. In fact, the whole plan

...coefficients. I have fixed this by defining my own statsModel (myLinearModel - imaginative) which also ignores such coefficients when predicting. The second problem I have is that I get "Cholesky not positive definite" errors at some nodes. I guess this is because of numerical error and degeneracy in the covariance matrix? Any thoughts on how to avoid having this happen would be welcome; it is ignorable though for now. The third and really big problem I have is that when I apply mob to large datasets (say hundreds of thousands of elements) I get a "logical subscript too long" erro...

...e it may be. Is it just a matter of expanding out the (1-L)^d term?) 2. I don't have access to the cited Haslett & Raftery (1989) paper, but could someone explain to me the little cautionary note in the help page stating that "nar and nma should not be too large (say < 10) to avoid degeneracy in the model." I see that a different implementation of the FARIMA procedure in Splus could lead to an explosive, ie. non-stationary model when it's used to fit a log volatility data set (Zivot & Wang, p.291). Zivot explains that it might be due to canceling roots in the AR and MA poly...

Hi, I am trying to estimate a quantile regression using panel data. I am trying to use the model that is described in Dr. Koenker's article. So I use the code the that is posted in the following link: http://www.econ.uiuc.edu/~roger/research/panel/rq.fit.panel.R How to estimate the panel data quantile regression if the regression contains no constant term? I tried to change the code of

G'Day R users! Following an ordination using prcomp, I'd like to test which variables singnificantly contribute to a principal component. There is a method suggested by Peres-Neto and al. 2003. Ecology 84:2347-2363 called "bootstrapped eigenvector". It was asked for that in this forum in January 2005 by J?r?me Lema?tre: "1) Resample 1000 times with replacement entire