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...blem is exactly. I imagine that it has something to do with "tyield" being a matrix. Any help on explaining what's going on and how to solve this is much appreciated. Thank you, Kristian library(FKF) #loading Fast Kalman Filter package library(Matrix) # matrix exponential package K_1 = 0.1156 K_2 = 0.17 sigma_1 = 0.1896 sigma_2 = 0.2156 lambda_1 = 0 lambda_2 = -0.5316 theta_1 = 0.1513 theta_2 = 0.2055 #test data tyield <- matrix(data = rnorm(200), nrow =2, ncol =100) # defining dimensions m <- 2 # m is the number of state variables n <- 100 # is the length of the obs...

...lt;- matrix(abs(rnorm(400)), nrow=10, ncol=40) m <- 2 # m is the number of state variables n <- ncol(x) # is the length of the observed sample d <- nrow(x) # is the number of observed variables. h <- 1/52 ## creating state space representation of 2-factor CIR model CIR2ss <- function(K_1, K_2, sigma_1, sigma_2, lambda_1, lambda_2, theta_1, theta_2, delta_0, delta_1, delta_2) { ## defining auxilary parameters, phi_11 <- sqrt((K_1+lambda_1)^2+2*sigma_1^2*delta_1) phi_21 <- sqrt((K_2+lambda_2)^2+2*sigma_2^2*delta_2) phi_12 <- K_1+lambda_1+phi_11 p...

...nd "class" (numeric). The latter runs from 1 to 78 and categorizes the data. I need to create a file "answer_1.txt" for the cases with class==1, and so on, up to "answer_78.txt" I have been able to do this for one value of "class" in the following way k_1<-answer[class==1] write.table(k_1, "answer_1.txt") Now, I would like to loop over "class", replacing the occurences of "1" in the code above successively with the integers from 1 to 78, so that I get my 78 files. (equivalent to typing: k_1<-answer[class==1]...

Hi, I wanted to know if there existed an good implementation in R of the following classical subset Integers : $P_{n,m} = {k_1, \ldots, k_m \in \mathbb{N} : k_1 + \ldots + k_m = n }$ for any integers $m < n$. There is an obvious not optimal code which would be to run through $m$ sums and put a boolean condition to report if the integers respect these condition but it would take $m^n$ steps... Thanks for your answers,...

Hi, I have a data-matrix: > PID sato hrs fim health 214 3 4.376430 6.582958 5 193 6 4.361825 3.138525 6 8441 6 4.205771 3.835886 7 7525 6 4.284489 3.245139 6 6806 7 4.168926 2.821833 7 5682 7 1.788707 1.212653 7 5225 6 1.651463 1.436980 7 4845 6 1.692710 1.267359 4 4552 5 1.686448 1.220539 6

..."h") all.perm_function(n){ p_matrix(1,ncol=1) for(i in 2:n){p_pp_cbind(p,i) v_c(1:i,1:(i-1)) for(j in 2:i){v_v[-1] p_rbind(p,pp[,v[1:i]])}} p} Until now I hesitated to dwell on writing functions to generate all n!/(k!(n-k)!) k-combinations of an n-element set or more generally all n!/(k_1!k_2!...n_k!) choices of placing n objects into k boxes where box j has n_j objects. Not intending to re-invent the wheel I turn to the R community to ask if someone has already written these functions. Any help is thankfully appreciated. --- D.Trenkler --- ***********************************...

Dear R users this may be a simple question - but i would appreciate any thoughts does anyone know how you would get one lower and one upper confidence interval for a set of data that consists of proportions. i.e. taking a usual confidence interval for normal data would result in the lower confidence interval being negative - which is not possible given the data (which is constrained between

Hello list. I'm trying to rebuild the 2.6.9.67.0.20.EL kernel, but it fails even without modifications. How did I try it? Created a (non-root) build environment (not a mock ) Installed the kernel.scr.rpm and did a rpmbuild -ba --target=`uname -m` kernel-2.6.spec 2> prep-err.log | tee prep-out.log The build failed at the end: Processing files: kernel-xenU-devel-2.6.9-67.0.20.EL Checking