[R] data.frame handling
Dear R-users, I have a little problem that I can't solve by myself. I have a data frame with 2 factors and 8 observations (see the following code): y - c(1,1,1,2,2,3,3,3) y - factor(y) levels(y) - c(a,b,c) x - c(1,2,3,1,2,1,2,3) x - factor(x) levels(x) - c(x,y,z) X - data.frame(factor1=x,factor2=y) and the final result is factor1 factor2 1 x a 2 y a 3 z a 4 x b 5 y b 6 x c 7 y c 8 z c From the above data I'd like to obtain the following matrix: a b c x 1 1 1 y 1 1 1 z 1 0 1 Do you have any advice? Can you help me please? Thank you in advance, Michela __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] spatio temporal plot
Dear R-users, I have a matrix of data (air pollution) with n rows and T columns, where n is the number of spatial locations and T is the number of time points (days of the year). I would like to use a 3d plot for plotting the n time series I have: so x-axis and y-axis are for the spatial coordinates and the z-axis is for the T air pollution data. But the final result should be like this: see the attached figure. It's like doing n vertical plots of the n time series and put them nearby using the spatial coordinates. Can you help me please? Thanks in advance, best regards Michela timeseriesplot.PNG Description: PNG image __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] double boostrap with clusterApplyLB
Dear R-Users,
we are using a linux-cluster with RMPI and the snow package.
We would like to do a double boostrap.
We have a general function that implements the first boostrap (the outer) and
we are wondering if we can include another bootstrap (the inner) in the
same general function including another clusterApplyLB.
For example:
general function = function(...) {
clusterApplyLB(cl, fun,...) }
where fun is the function for the inner boostrap
outer bootstrap = clusterApplyLB(cl,general function,...)
Does R accept this kind of expression?
Thank you very much in advance,
Michela and Marco
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[R] loading libraries on MPI cluster
Dear R-users, we are using library(snow) for computation on a linux cluster with RMPI. We have a problem with clusterEvalQ: after launching clusterEvalQ it seems loading the required library on each node but if we type a function belonging to the loaded package R doesn't find it. library(snow) # making cluster with 3 nodes cl - makeCluster(3, type = MPI) Loading required package: Rmpi 3 slaves are spawned successfully. 0 failed. #loading library abind on each node clusterEvalQ(cl,library(abind)) [[1]] [1] abind EMsspir mvtnorm MASS snow Rmpi [7] methods stats graphics grDevices utils datasets [13] base [[2]] [1] abind EMsspir mvtnorm MASS snow Rmpi [7] methods stats graphics grDevices utils datasets [13] base [[3]] [1] abind EMsspir mvtnorm MASS snow Rmpi [7] methods stats graphics grDevices utils datasets [13] base #searching for function abind belonging to library abind abind Error: object abind not found Is it possible to know which libraries each node has loaded? Thank you very much best regards Michela and Marco __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Rmpi performance
Dear R users,
we are trying to do some parallel computing using library(snow).
In particular we have a cluster with 3 nodes
cl - makeCluster(3, type = MPI)
3 slaves are spawned successfully. 0 failed.
and we want to compute the function op_mat (see below) first with the
master and then with the cluster using system.time for checking the
computational performance.
op_mat = function(mat) {
+ inv = solve(mat)
+ det_inv = det(inversa)
+ tr_inv = sum(diag(inversa))
+ return(list(c(det=det_inv,tr=tr_inv)))
+ }
nn = 3000
XX = matrix(rnorm(nn*nn),nn,nn)
# with the master
system.time(op_matrici(XX))
[1] 42.283 1.883 44.168 0.000 0.000
# with the cluster
system.time(clusterCall(cl,op_matrici,XX))
[1] 11.523 12.612 71.562 0.000 0.000
You can see that using the master it takes 44.168 seconds for computing
the function on matrix XX while it takes 71.562 seconds (more time!!!)
with the cluster. Can you give us some advice in order to understand why
the cluster is slower than the master?
Thank you very much in advance,
bye
Michela and Marco
Ps: we have a gigabit ethernet between the master and the nodes
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and provide commented, minimal, self-contained, reproducible code.
[R] SSPIR problem
Dear R-Users, I'm using SSPIR package for a spatio-temporal application. Is it possible to modify the structure of the involved matrixes (Fmat, Gmat, Vmat,Wmat)? I want to create a model like this #y(t)=k*theta(t)+epsilon(t) #theta(t)=h*theta(t-1)+eta(t) #epsilon(t) N(0,V) V=sigma2*I #eta(t) N(0,W)W=sigma2_eta where the state variable theta has dimension 1(p=1) and at each time time the observed variable y has dimension equal to d=3. Moreover I want to use white noise errors. But with the command SS(y) where y is my nXd data matrix (d=observations at each time, n=numbers of time points) I obtain a different model. Can you help me please? Thanks in advance Michela __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] SSPIR problem
Dear R-Users, I'm using SSPIR package for a spatio-temporal application. Is it possible to modify the structure of the involved matrixes (Fmat, Gmat, Vmat,Wmat)? I want to create a model like this #y(t)=k*theta(t)+epsilon(t) #theta(t)=h*theta(t-1)+eta(t) #epsilon(t) N(0,V) V=sigma2*I #eta(t) N(0,W)W=sigma2_eta where the state variable theta has dimension 1(p=1) and at each time time the observed variable y has dimension equal to d=3. Moreover I want to use white noise errors. But with the command SS(y) where y is my nXd data matrix (d=observations at each time, n=numbers of time points) I obtain a different model. Can you help me please? Thanks in advance Michela __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] EM algorithm
Dear R-Users, I have a model with a latent variable for a spatio-temporal process. I would like to use EM algorithm to estimate the parameters. Does anybody know how to implement the algorithm in R? Thank you very much in advance, Michela __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
