similar to: Greek symbols in xtable rows

Dear everyone, I've got difficulties in realizing the following task: I have two vectors: A <- c(1:10) B<- seq(1,10,2) Now I want to make a table form vectors A and B as rows, and if a value of A isn't present B, then I want to put a N/A symbol in it: Output should look like this: 1 2 3 4 5 6 7 8 9 10 1 0 3 0 5 0 7 0 9 0 How can I do this in R? Thank you. -- Andris

Dear R users, When running the program below I receive the following error message: fit <- optim(parm, objective, yt = tyield, hessian = TRUE) Error in as.vector(data) : no method for coercing this S4 class to a vector I can't figure out what the problem is exactly. I imagine that it has something to do with "tyield" being a matrix. Any help on explaining what's going on

Hi, I'm trying to estimate the parameters of a state space model of the following form measurement eq: z_t = a + b*y_t + eps_t transition eq y_t+h = (I -exp(-hL))theta + exp(-hL)y_t+ eta_{t+h}. The problem is that the distribution of the innovations of the transition equation depend on the previous value of the state variable. To be exact: y_t|y_{t-1} ~N(mu, Q_t) where Q is a diagonal

Hello all (especially MCLUS users). I'm trying to make use of the MCLUST package by C. Fraley and A. Raftery. My problem is trying to figure out how the (model) identifier (e.g, EII, VII, VVI, etc.) relates to the covariance matrix. The parameterization of the covariance matrix makes use of the method of decomposition in Banfield and Rraftery (1993) and Fraley and Raftery (2002) where

Dear R-Users I would like to estimate a constrained bivariate normal density, the constraint being that the means are of equal magnitude but of opposite signs. So I need to estimate four parameters: mu (meanvector (mu,-mu)) sigma_1 and sigma_2 (two sd deviations) rho (correlation coefficient) I have looked at several packages, including Gaussian mixture models in Mclust, but I am not sure

Hi all, I'd like to fit a multivariate regression with the variance of the error term porportional to the predictors, like the WLS in the univariate case. y_1~x_1+x_2 y_2~x_1+x_2 var(y_1)=x_1*sigma_1^2 var(y_2)=x_2*sigma_2^2 cov(y_1,y_2)=sqrt(x_1*x_2)*sigma_12^2 How can I specify this in R? Is there a corresponding function to the univariate specification lm(y~x,weights=x)??

Hello useRs, I can't figure out how can I store a data frame of values of X and D from this loop: Z <- c(1:10) for (i in 1:(length(Z)-2)) {D <- x[1:(2+i)]; X <- paste("x",sep="",i) print (X) print (D) } Thank You, Andris Jankevics

Hi all, I have a vector which contains many repeated values. >Z <- c(1,2,3,4,5,1,2,3,4,5,1,2,3,5,5,2,3,4,5) I need to know how many times each number in this vecetor is repeated. I can use a command like this: > table (cut(Z,seq(1,5,1))) (1,2] (2,3] (3,4] (4,5] 4 4 3 5 But how can I find a break points for vector with random values and random number sequence

Thanks Andris, Michael and Petr for your prompt and kind feedbacks. I will try generating my own biplot from low-level graph commands... I hope it will work. Best regards, Marco -- Marco Manca, MD University of Maastricht Faculty of Health, Medicine and Life Sciences (FHML) Cardiovascular Research Institute (CARIM) PO Box 616 6200 MD Maastricht E-mail: m.manca at path.unimaas.nl Office

Is there any generic function that gets the "home" directory? This should return /home/<user> in Linux and x:/Documents and Settings/<user> (or whatever) in Windows XP. Another (unrelated) question: what is the _simplest_ way to read and write R variables to/from files such that they are stored in a human-readable but R-like form? For example, if (say), x is a vector

Hi, I read the howto of iproute, I have the same case with HOWTO, the difference is that the whole incoming traffic goes through interface 0, the other difference is that I do not want to balance the out going traffic, because I have specific networks to take it throughout another interface. Mi Case IF1 --> Input and Output IF2 --> Only aoutput for three Network I need Help, How can I

Hi all, I'm trying to define and log-likelihood function to work with MLE. There will be parameters like mu_i, sigma_i, tau_i, ro_i, for i between 1 to 24. Instead of listing all the parameters, one by one in the function definition, is there a neat way to do it in R ? The example is as follows: ll<- function(mu1=-0.5,b=1.2,tau_1=0.5,sigma_1=0.5,ro_1=0.7) { if (tau1>0 &&

I keep getting the 'memory.size' error message when I run a program I have been writing. It always it cannot allocate a vector of a certain size. I believe the error comes in the code fragement below where I have multiple arrays that could be taking up space. Does anyone know a good way around this? w1 <- outer(xk$xk1, data[,x1], function(y,z) abs(z-y)) w2 <- outer(xk$xk2,

Hi, I have some big calculations in R to be done. Since I can use R on a server with ssh, i was wondering if I can reopen a R Shell after exiting ssh. I don't want to use the batch mode and nohup doesn't work. I want to use something like ssh user at server R ---do something in R and start calculation --- close ssh but let R remain on the server, doing the calculation ssh user at

I would like to run a for loop with an index going from 0 to 499 but the following seems to miss out the first value: C <- 499 for (i in 0:C) The alternative is: C <- 500 for (i in 1:C) { #Then every time I use i, I replace it with i-1 } Is this a good way to do it or is tere a better way? Thank you, ThomasThis message and any attachment are intended solely for the addressee and may

Hi, I wrote some simple rpanel package script for visual spectral data comparison. At this example i have a three samples and i want to zoom through x and y axis to compare differences between samples. With my script below I can zoom to some data region and add some other spetra to the plot, through text input field. But I can't figure out, how to change axis scaling for all displayed

Dear all, I am trying to my dataframe for the PLS analysis using the PLS package. However I have some trouble generating the correct dataframe. The main problem is how to use one name to represent several columns in the dataframe. The example dataframe in PLS package is called "sensory". I cannot directly read the data file since it's a binary file. If I use

Hello, I have a large data matrix (68x13112), each row corresponding to one observation (patients) and each column corresponding to the variables (points within an NMR spectrum). I would like to carry out some kind of clustering on these data to see how many clusters are there. I have tried the function clara() from the package cluster. If I use the matrix as is, I can perform the clara

All, I am working with NIR spectral data and it was great to find that the example in ?plsr also used spectral data. Unfortunately, I am having difficulty figuring out how the "yarn" dataset is structured to allow for the plsr model to read: library(pls) data(yard) yarn.oscorespls <- mvr(density ~ NIR, 6, data = yarn, validation = "CV", method = "oscorespls")

Hi, Using indicator variables I have been able to fit and run the code for fitting a bivariate mixed model using unstructured covariance matrix The code is lme.fit1<- lme(one.var~-1+indic1+indic2+I(indic1*d.time)+I(indic2*d.time), random =~ -1+indic1+indic2|m.unit, weights = varIdent(~1|indic1) ,data = new.data) My variables are one.var :- the two response variables stacked one after