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Well, I could argue that it's not *completely* OT since my question is motivated by an enquiry that I received in respect of a CRAN package "Iso" that I wrote and maintain. The question is this: Given observations y_1, ..., y_n, what is the solution to the problem: minimise \sum_{i=1}^n (y_i - y_i^*)^2 with respect to y_1^*, ..., y_n^* subject to the "isotonic" constraint y_1^* <= y_2^* <= ... <= y_n^* and the *additional8 bound constraint a <= y_1^* and y_n^* <= b, where a and b are given c...

Dear All, Here is what I am trying to achieve: I would like to plot some data in 3D. Usually, one has a matrix of the kind y_1(x_1) , y_1(x_2).....y_1(x_i) y_2(x_1) , y_2(x_2).....y_2(x_i) ........................................... y_n(x_1) , y_n(x_2)......y_n(x_i) where e.g. y_2(x_1) is the value of y at time 2 at point x_1 (see that the grid in x is the same for the y values at all times). Instead, in my case, the quantity y is observed at each time on a different grid in x; in other words not only do I have a different nu...

...This is most likely only a minor technicality, but I saw the following: On page 6 of the 'parallel' vignette (http://stat.ethz.ch/R-manual/R-devel/library/parallel/doc/parallel.pdf), the random-number generator "L'Ecuyer-CMRG" is said to have seed "(x_n, x_{n-1}, x_{n-2}, y_n, y_{n-1}, y_{n-2})". However, in L'Ecuyer et al. (2002), the seed is given with 'increasing' indices, so should rather be "(x_{n-2}, x_{n-1}, x_n, y_{n-2}, y_{n-1}, y_n)" (or, even more intuitively, "(x_{n-3}, x_{n-2}, x_{n-1}, y_{n-3}, y_{n-2}, y_{n-1})"). The...

Dear Sir/Madam, I apologize for any cross-posting. I got a simple question, which I thought the R list may help me to find an answer. Suppose we have Y_1, Y_2, ., Y_n ~ Poisson (Lambda_i) and Lambda_i ~Gamma(alpha_i, beta_i). Empirical Bayes Estimator for hyper-parameters of the gamma distr, i.e. (alpha_t, beta_t) are needed. y=c(12,5,17,14) n=4 What about a Hierarchal B ayes estimators? Any relevant work and codes in R (or S+) is highly apprec...

Hi, I have to draw samples from an asymmetric-Laplace-Normal distribution: f(u|y, x, beta, phi, sigma, tau) \propto exp( - sum( ( abs(lo) + (2*tau-1)*lo )/(2*sigma) ) - 0.5/phi*u^2), where lo = (y - x*beta) and y=(y_1, ..., y_n), x=(x_1, ..., x_n) -- sorry for this huge formula -- A WinBUGS Gibbs sampler and the HI package arms sampler were used with the same initial data for all parameters. I compared the mean from both the Gibbs sample and the arms sample for several y and x. Surprisingly, both means always differed by...

...only a minor technicality, but I saw the > following: On page 6 of the 'parallel' vignette > (http://stat.ethz.ch/R-manual/R-devel/library/parallel/doc/parallel.pdf), > the random-number generator "L'Ecuyer-CMRG" is said to have seed > "(x_n, x_{n-1}, x_{n-2}, y_n, y_{n-1}, y_{n-2})". However, in L'Ecuyer > et al. (2002), the seed is given with 'increasing' indices, so should > rather be "(x_{n-2}, x_{n-1}, x_n, y_{n-2}, y_{n-1}, y_n)" (or, even > more intuitively, "(x_{n-3}, x_{n-2}, x_{n-1}, y_{n-3}, y_{n-2}, > y...

...the lm() command? For instance, imagine that we have the following data set (the number of observations for each company is actually larger than the one showed...): Company Y X1 X2 1 y_1 x1_1 x2_1 1 y_2 x1_2 x2_2 1 y_3 x1_3 x2_3 (...) 2 y_4 x1_4 x2_4 2 y_5 x1_5 x2_5 2 y_6 x1_6 x2_6 (...) n y_n x1_n x2_n n y_n1 x1_n1 x2_n1 n y_n2 x1_n2 x2_n2 (...) I need to run a regression of Y=b0+b1*X1+b2*X2 for EACH company in the dataset and then retrieve the coefficients for each regression obtained (and t-stats and R^2) for each company and put it in another dataset/table. The procedure can be do...

Good morning to you all, Sorry for taking your time from your research and teaching schedules.   If you have a non-stationary univariate time Series data that has the transformation: Say; l.dat<-log (series) d.ldat<-diff (l.dat, differences=1) and you fit say arima model. predit.arima<-predict (fit.series, n.ahead=10, xregnew= (n+1) :( n+10)) How could I re-transform

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