search for: reestim

Dear List: I am working to construct a matrix of a particular form. For the most part, developing the matrix is simple and is built as follows: vl.mat<-matrix(c(0,0,0,0,0,64,0,0,0,0,64,0,0,0,0,64),nc=4) Now to expand this matrix to be block-diagonal, I do the following: sample.size <- 100 # number of individual students I<- diag(sample.size) bd.mat<-kronecker(I,vl.mat) This

Hi, What I'm trying to achieve is very fast algorithm for fitting logistic regression model. I have to estimate regression coeficients using about 10k observations. Once I have coefficients estimated, new 100 rows of data becomes available.... Now I need to reestimate coeficients using 100 newly arrived observations and removing 100 oldest observations. So, my question is would it be possible to somehow reuse pre iusly calculated coeficients and only adjust them cor newly arrived data? I know it would have to be some aproximation but I suppose it will be goo...

Dear List: I am estimating a gls model and am having to make some rather unconventional modifications to handle a particular problem I have identified. My aim is to fit a GLS with an AR1 structure, obtain the variance-covariance matrix (V), modify it as needed given my research problem, and then reestimate the GLS by brute force using matrix operations. All seems to be working almost perfectly, yet there is one small issue that I cannot seem to resolve and would appreciate any thoughts on my problem. I have developed some code for simulating a longitudinal analysis of student achievement test sc...

...I'm using lm() to do the estimation. I plan to change the model and possibly the method once I've seen if forecasting works. The current model "works" moderately well for in-sample fits, though I suspect there is too much variability generally. I want to advance 1 week at a time, reestimate, and iterate. This is a test case where we know the "future". I can get this to work for a few weeks starting at 20041101, but then get an error msg "new factor levels in 'events' ...". I have tried putting drop.factor.levels = TRUE in predict(), but this didn'...

I used to consider using R and "Optim" to replace my commercial packages: Gauss and Matlab. But it turns out that "Optim" does not converge completely. The same data for Gauss and Matlab are converged very well. I see that there are too many packages based on "optim" and really doubt if they can be trusted! -- View this message in context:

...d dispatch etc.) as possible. I do want to have the choice if I'm carrying (possibly loads of) data with me in the fields of my object or if I compute/get them based on some function whenever I actually need it. For example, I'm thinking about parameter estimates that could automatically be reestimated based on rules that take into account a constantly changing data structure (new observations come it quite frequently or something like that). What do you think of the way I've implemented this? Does this make sense to you or is something like this done in another (and probably more elega...

...ethod dispatch etc.) as possible. I do want to have the choice if I?m carrying (possibly loads of) data with me in the fields of my object or if I compute/get them based on some function whenever I actually need it. For example, I'm thinking about parameter estimates that could automatically be reestimated based on rules that take into account a constantly changing data structure (new observations come it quite frequently or something like that). What do you think of the way I?ve implemented this? Does this make sense to you or is something like this done in another (and probably more elegant ;...

Dear all, I am planning to use nlme library for analysis of experiments in semiconductor industry. Currently I am using "lm" but plan to move to "lme" to handle within wafer / wafer-to-wafer and lot-to-lot variation correctly. So far everything is working well, but I have a fundamentel question: NLME offers "maximum likelihood" and "restricted maximum