similar to: Variance

I currently have this code: for(j in 2:n){ for(i in 1:(j-1)){ # Make sure the inputs are for the matrix "m" input1=rownames(m)[i] input2=colnames(m)[j] q=t[(t$Rec1==input1 & t$Rec2==input2),output] if(length(q)==0){ q=t[(t$Rec1==input2 & t$Rec2==input1),output] } m[i,j]=mean(q) m[j,i]=mean(q) m[j,j]=mean(q) }} I already created a

I have a Sun Clutster running on two Sun Fire 4800s, OS is Solaris 9. The environment was set up with PC Netlink prior to my arrival. On Nov 24 after work I shutdown PC Netlink on both systems and started Samba. However from the windows side we can only see one Sun box and the one sun development box that I tested on prior to this weekend. The other production system can't be seen from

Hi, I just bumped into a bug in this code. The problem was as follows: I have defined a set of registers with rather similar names including digits. The code section at RegisterInfoEmitter::run(){ ... // Process sub-register sets. runs and fills the RegisterAliases map. then, ... for (unsigned i = 0, e = Regs.size(); i != e; ++i) { RegNo[Regs[i].TheDef] = i; NumAliases +=

Hi everyone, I'm involved in a discussion with a colleague. He suggested a sample design for a finite-sized process that (to all intents and purposes) involves tossing a coin and examining the unit if the coin shows Heads. I should emphasize that we're both approaching the problem from a design-based sampling theory point of view. So I have no argument about the appropriateness of the

Hi everyone, I know there have been several requests regarding subsetting before, but none of them really helps with my problem: I'm trying to subset only infected individuals from the REC2 data.frame: > str(REC2) 'data.frame': 362 obs. of 7 variables: $ RINGNO : Factor w/ 370 levels "BL17546","BL17577",..: 78 81 67 41 58 66 17 $ year : Factor w/ 8

This is part of my program. I am getting an error, that I cannot figure out, any help would very much appreciated, thanks. # subset variables arc <- arc[,c("SNAP", "code", "ncode", "var", "n_total")] Error in `[.data.frame`(arc, , c("SNAP", "code", "ncode", : undefined columns selected arc$N_eff <-

Dear all, I am facing the following problem in optimization: w = (d, o1, ..., op, m1, ..., mq) is a 1 + p + q vector I want to determine: w = argmin (a - d(w))' A (a - d(w)) where a is a 1xK marix, A is the covariance matrix of vector a, d(w) is a 1xK vector which parameters are functions of parameters d, o1 .. op, m1 .. mq. Is there some function to solve this problem easily? I know

The R "cut" command is entirely different from the UNIX "cut" command. The latter retains selected fields in a line of text. I can do that kind of manipulation using sub() or gsub(), but it is tedious. I assume there is an R function that will do this, but I don't know its name. Can you tell me? I'm also guessing that there is a web page somewhere that will tell

Hi, How i can install the package "adapt" in some version of R for mac? i try in 2.13, 2.9,2.7 and other previous versions... and nothing happens. and another question: There are some packages that do the same but that it is implemented for mac? (calculate integrals in 2 or more dimmensions). help me please, it's for an important work. greetings. -- Matías Hernán Ramírez

Hello. I'm trying to use the functions pandit and treebase. They are in the package apTreeshape. Once I've loaded the package, R responses: - no function pandit/treebase. Somebody knows why or what is the reason? Thanks, Arnau. ------------------------------------------------------------ Arnau Mir Torres Edifici A. Turmeda Campus UIB Ctra. Valldemossa, km. 7,5 07122 Palma de Mca.

I am wondering how to obtain the model/equation at each level automatically in a regression model with a few factors without looking at summary of the lm model. For example, consider lm.factors <- lm(y ~ x1 + factor(x2)*factor(x3)+x4*factor(x5)) The coefficients of lm.factors in summary(lm.factors) might be complicated. I would like to have the equation at each level from lm.factor. Could you

Hi, I have three matrices (X,Y,P) with the same dimension. The X,Y grid is regular and I want to perform linear interpolation to pick out certain points. In matlab appropriate call is something like Pout=interp2(X,Y,P,Xout,Yout, method="linear") where Xout and Yout are the locations where I want the Pout data (typically a different grid). (Scipy has this routine in

I'm fitting a regression model for censored data with three categorical predictors, say A, B, C. My final model based on the survreg function is Surv(..) ~ A*(B+C). I know the three-way group mean estimates can be computed using the predict function. But is there any way to obtain two-way group mean estimates, say estimated group mean for (A1, B1)-group? The sample group means don't

Dear community, I uploaded an excel with read.xls. My xls file actually have a column which is an id, ("plot" is the id) : plot height area 34 7.6 5.4 85 3.2 4.1 89 5.4 8.4 121 6.7 6.2 ... 1325 2.1 1.5 However R uses another id, this way: r id plot height area 1 34 7.6 5.4 2 85 3.2 4.1 3 89 5.4 8.4 4 121

I have a vector with lots of different numbers. I need to make a graph showing the Uniform Distribution of the figures. I have created a graph showing all the different values, but now want individual Gaussian Kernel round each point. This is what I have but each time it comes up with an error as I have just based it on the Normal Distribution, but I'm not sure what I need to change to make it

Hi, Can someone please offer me some guidance? I imported some data. One of the columns called "JOBTITLE" when imported was imported as a factor column with 416 levels. I subset the data in such a way that only 4 levels have data in "JOBTITLE" and tried running randomForest but it complained about "JOBTITLE" having more than 32 categories. I know that is the limit

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Hi, I am attempting to fit a ARMA/GARCH regression model without success. ### ARIMA-GARCH model with regressor ### ### Time series data: A multivariate data set. cov.ts.dq = cov.ts[1:4,"dq1"][!is.na(cov.ts[,"dq1"])] cov.ts.day = ts.intersect(dq = diff(q.ts), day = lag(q.ts, -1)) ### The following R scripts work: (summary(no.day.fitr <- garchFit(dq ~ arma(0,3) +

Hi everybody I couldn't find the solution to what must be quite a simple problem. Maybe you can help? treatment session period stage wage_accepted market 1 1 1 1 1 25 public 2 1 1 1 1 19 privat 3 1 1 1 1 15 public 4 1

Hi, Is it possible (i am sure it is) to subset data from a data.frame on the basis of SQL >LIKE< operator. I.e., i would like to subset a data where only values which contains a string >GP< would be used? Example: Gp<-subset(DF, DF$USCS like >GP<) This like of course is not working, Thanks, m [[alternative HTML version deleted]]