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...ve a name, and 2) are the usual SRS formula for e.g. the standard error of the mean exactly accurate? Or are they defensibly accurate approximations? 3) can anyone suggest some citations that provide guidance either way? Thanks for any assistance! Andrew -- Andrew Robinson Program Manager, ACERA Department of Mathematics and Statistics Tel: +61-3-8344-6410 University of Melbourne, VIC 3010 Australia (prefer email) http://www.ms.unimelb.edu.au/~andrewpr Fax: +61-3-8344-4599 http://www.acera.unimelb.edu.au/ Forest Analytics with R (Springer, 2011) htt...

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

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 <-

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

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

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

I'm trying to find the variance of various outputs in a matrix: for(l in 2:vl){ for(o in 1:(l-1)){ # Make sure the inputs are for the matrix "m" input3=rownames(v)[o] input4=colnames(v)[l] r=t[(t$Rec1==input3 & t$Rec2==input4),output] if(length(r)==0){ r=t[(t$Rec1==input4 & t$Rec2==input3),output] } v[l,o]=var(q,na.rm=TRUE)

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]]

Hi, I have a erdos-renyi game with 6000 nodes and probability 0.003. g1 = erdos.renyi.game(6000, 0.003) How to create a Watts Strogatz game with the same probability. g1 = watts.strogatz.game(1, 6000, ?, ?) What should be the third and fourth parameter to this argument. -- View this message in context: http://r.789695.n4.nabble.com/Watts-Strogatz-game-tp3491922p3491922.html Sent from the R

I have the following data set, and I have to find the line of best fit using this equation, y = a*(1 - exp(-b*x)). samples = seq(1,20,by=1) species = c(5,8,9,9,11,11,12,15,17,19,20,20,21,23,23,25,25,27,27,27) plot(samples,species, main = "Accumulation Curve for Tree Species Richness", xlab = "Samples", ylab = "Number of Species") curve((y = 27*(1 -

I am attempting to use package boot to summarize and compare the performance of three models. I'm using R 2.13.0 in a Win32 environment. My statistic function returns a vector of 6 values, 3 of which are error rates for different models, and 3 are pairwise differences between those error rates. It looks like: multiEst<-function(dat,i) { .... c(E1,E2,E3,E2-E1,E3-E1,E3-E2); }