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Hello! I am having a problem understanding what the weights option in the locfit command of the locfit package is doing. I have written a sample program which illustrates the issue (below). The example involves using bootstrap however, that is not my main goal but it illustrates where my problem lies. As you know, to compute a bootstrap estimate of a particular quantity using a sample size of

Hi everybody, This has been causing me some trouble: I want to combine several lists of pairs into a single?vector but keep the pairs together. The lists are of the form: (1)?x1 x2 x3... N? (2) y1 y2 y3..? N I would like to keep it this way, simply appending one list to another, e.g. (1) x1i x2i... x1j x2j... N (2) etc. A?method like c(...) does not achieve this. It creates a single list,

Hi Dr. Viechtbauer, I'm doing meta-analysis using your package 'metafor'. I used the 'IRFT' to transform the incident rate. But when I tried to back-transform the summary estimates from function rma, I don't know what's the appropriate ti to feed in function transf.iirft. I searched and found your post about using harmonic mean for ni to back-transform the double

I am using the gls function to fit a two-stage least squares model with first order autoregressive error terms. Since there is no automated adjustment for the use of two-stage least squares in this package, I am trying to manually replicate standard errors of the coefficient estimates in order to adjust for a first stage OLS estimate of endogenous variables. However, thus far I have been unable to

Dear all, I get an error using betrag on this data set :http://dl.dropbox.com/u/1866110/dump.csv. I run it like this regression f2.1=betareg(Y~X1+X2,data=dump) summary(f2.1) I get : Call: betareg(formula = Y ~ X1 + X2, data = dump) Standardized weighted residuals 2: Error in quantile.default(x$residuals) : missing values and NaN's not allowed if 'na.rm' is FALSE In addition:

Dear all, I have a couple of short noob questions for whoever can take them. I'm from a very non-stats background so sorry for offending anybody with stupid questions ! :-) I have been using logistic regression care of glm to analyse a binary dependent variable against a couple of independent variables. All has gone well so far. In my work I have to compare the accuracy of analysis to a C4.5

[mod: Forwarded by Jeff Uphoff. I tried to mangle the headers that it appears as the original post: with an invalid return address. -- REW] A few months back, a very alpha version of bliss got posted. That shouldn''t have happened, but, it was pretty much ignored so I didn''t worry about it. But now it seems there''s a bit of a fuss about this. I''ll post the

Hi, if i have data in the following time series format: time, amount, state 1 2222 A 1 333 B 2 45 A 2 77 B where states could be n and time periods t is there a package in R that would calculate the transition probabilities in a markov chain. for each t except t=0 to generate A B A B perhaps the best structure might

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