search for: par2

Hello, unfortunately, I don't know a better subject. I would like to be very flexible in how to process my data. Assume the following dataset: par1 <- seq(0,1,length.out = 100) par2 <- seq(1,100) fac1 <- factor(rep(c("group1", "group2"), each = 50)) fac2 <- factor(rep(c("group3", "group4", "group5", "group6"), each = 25)) df <- data.frame(par1, par2, fac1, fac2) Now, I would like to calculate e.g. the &q...

Hi, I wonder how to pass several functions and their arguments as arguments to a function. For example, the main function is f = function(X ) { process1(X) ... process2(X) } I have a few functions that operate on X, e.g. g1(X, par1), g2(X, par2), g3(X, par3). par1, par2 and par3 are parameters and of different types. I would like to pass g1, g2, g3 and their arguments to f and g1, g2, g3 may appear to be in different orders. So that final effect of the passing is f = function(X ) { process1(X) g1(X, par1) g2(X, par2) g3(X,...

...ith you for two reasons: - Maybe others come across the same problem. - Maybe someone has a much simpler solution that wants to share with me ;-) The problem is as follows: expand.grid() allows you to generate a data.frame with all combinations of a set of values, e.g.: > expand.grid(par1=-1:1,par2=c('a','b')) par1 par2 1 -1 a 2 0 a 3 1 a 4 -1 b 5 0 b 6 1 b There is nothing wrong with this nice function except when you have too many combinations to fit in your computer memory, and that was my problem: I wanted to do something for each com...

...know1 = c("Y","N","N","Y","N","N","Y","Y","N") par1=c(1,4,5,3,3,2,3,3,5) know2 = c("Y","Y","N","Y","N","N","N","Y","Y") par2=c(3,4,4,3,5,2,4,3,2) DATA=data.frame(know1,par1,know2,par2) it represents answers in a questionnaire, where respondents evaluate two things (par1 and par2) but they also indicate, whether they have detailed knowledge about those two things (know1 and know2). I need to test correlations between...

...(x$pending) > bitmap(file="tmp") > densityplot(~y,col="black",main="x") > dev.off() Basically, they are the same lines inside the script, I got the expected output. I appreciate you advice, The script code: totalgraphics <- function(server,status) { par2 = '0' par1 = '0' filename <- paste(server,status,sep='.') filename <- paste('./pre-processed/',filename,sep='') v <- read.csv(file=filename,sep=',') x <- v[[status]] par1 <- as.numeric(par1) par2 <- as.numeric(par2) x <- as.ts(x)...

...d after I run this (as a script from a file). I thought that theta would contain the fitted parameters. The goal here is to find the least squares fit according to the function defined as "rss" subject to the constraints defined as ui and ci. I defined ui and ci to (hopefully) force par2 and par3 into the range 0.0 <= par2 <= 1.0 and 0.0 <= par3 <= 1.0. I am not at all sure that ui and ci are defined correctly. The call to constrOptim returns normally, but without a solution (apparently). Any suggestions appreciated. Thanks Stu # data y <- c(0.111111...

...ld i know what to ask\nif the person answering was you\n\n(Ernst Jandl, stanzen)") dev.off() > windows(width=width, height=height, rescale="R") > > ## changing par(cex=) alone does NOT change par("csi") > par(cex=1) > par1 <- par() > par(cex=2) > par2 <- par() > all.equal(par1, par2) [1] "Component cex: Mean relative difference: 1" > par1$cex [1] 1 > par2$cex [1] 2 > > ## changing par(cex=) and par(mai=) DOES change par("csi") > par(cex=1) > par(mai=oldmai) > par1 <- par() > par(cex=2) >...

Hi R users: I'm trying to make a function where two of the parameters are functions, but I don't know how to put each set of parameters for each function. What am I missing? I try this code: f2<-function(n=2,nsim=100,fun1=rnorm,par1=list(),fun2=rnorm,par2=list()){ force(fun1) force(fun2) force(n) p1<-unlist(par1) p2<-unlist(par2) force(p1) force(p2) localfun1 <- function() fun1(n, p1) localfun2 <- function() fun2(n, p2) vp<-replicate(nsim,t.test(localfun1(), localfun2())$p.value) return(vp)...

Dear R users: I have a problem about catch the value from function. I have following two functions (part): sbolus1 <- function() { ....... for( i in 1:Subject) { kel<-par1 Vd<-par2 PKindex<-sbolus1.out(PKtime,kel,Vd,defun,par1,par2,Dose,i) } savefile(PKindex) } sbolus1.out<-function(PKtime,kel,Vd,defun,par1,par2,Dose,i) { time<-PKtime$time parms<-c(kel=kel,Vd=Vd) C1.lsoda<-data.frame(lsoda(Dose/Vd,c(0,time),defun,parms)) cat(&quot...

...am using DEoptim package to pick the most optimal start values - fm4 <- function(x) x[1] + x[2]*exp(x[3] * -dist) + x[4]*exp(x[5] * -dist) fm5 <- function(x) sum((wcorr-fm4(x))^2) fm6 <- DEoptim(fm5, lower=c(0,0.1,1,0.1,1), upper=c(10e7, 100, 300,100, 300 ), control=list(trace=FALSE)) par2 <- fm6$optim$bestmem names(par2) <- c("c", "A", "n1", "B", "n2") fit2 <- nls(wcorr ~ (c + A*exp(n1 * -dist) + B*exp(n2 * -dist)), start=par2,control =list(maxiter=1000, warnOnly=TRUE)) However, I keep getting the following error - Error...

Does anyone know if the pan news reader works on CentOS 5.4? I am considering installing version 0.132 that I downloaded from pan.rebelbase.com . Thanks for your advice. Mike.

...=value) and getOption("par") I was aking myselft what would be the "better" strategy to handle a bunch of options for a package. I ended up with the idea of storing a list, as my options would also be classified, with something like: -- MyPkgOptions = list(set1=list(par1=1,par2=2),set2=list(subset1=list(par1=11,par2=22),subset2=list(par1=111,par2=222))) options(PkgName=MyPkgOptions) -- Then, to make easier the access to an element, I tweaked a little bit getOption, with the following version: -- getOption <- function(x,...) { op = options(x)[[1]] if (length(li...

Hi there again, I have a problem with the "parse"-command. First of all, I show you in a simplified way, what I am trying to do and what "R" answers: > test [1] "u.g$par1, u.g$par2" > mode(test) [1] "character" > ausdruck <- parse(text = test) Error in parse(file, n, text, prompt) : syntax error in "u.g$par1," That is what I did and I can't find the mistake. I just want to have "test" without quotes (to do eval(ausdruck...

Hi, I wonder how to pass several functions and their arguments as arguments to a function. For example, the main function is f = function(X ) { process(X) ... process(X) } I have a few functions that operate on X, e.g. g1(X, par1), g2(X, par2), g3(X, par3). par1, par2 and par3 are parameters and of different types.

...ives an error which is due to the outer function. I have tested the program with another simpler function and it works. So, I know that the problem is in the function that I have written.  Below I copy the error and the part of the program (the function) which causes the error:   Error: outer(par1, par2, y1, y2, FUN = function.subplot, KERNEL = KERNEL,: dims [product 25921] [1] does not match the length of the object.     par1 <- seq(-3,3,0.1) par2<- seq(-3,3,0.1) x<-cbind(par1,par2)       # par1:parameter1, par2: parameter2, sigma is the third parameter that I fix densityfunction <- f...

...es someone know how to get std.coef to show the standard error of the standardized path coefficients as well? Thanks, Bastiaan PS: When I use std.coef, all I get is this: std.coef(path.model.SSI4) Std. Estimate par1 par1 0.39499 com_veg <--- tempm par2 par2 0.35231 SNutBili <--- tempm par3 par3 -0.68170 S_SSI4 <--- tempm par4 par4 -0.39145 com_veg <--- Wdeficit par5 par5 -0.60025 SNutBili <--- Wdeficit par6 par6 -0.20562 S_SSI4 <--- Wdeficit par7 par7 0.14871 SNutBili <--- com_veg par8...

Dear all, Using: library(vegan) data(BCI) mod <- radfit(BCI[1,]) mod RAD models, family poisson No. of species 93, total abundance 448 par1 par2 par3 Deviance AIC BIC Null 39.5261 315.4362 315.4362 Preemption 0.042797 21.8939 299.8041 302.3367 Lognormal 1.0687 1.0186 25.1528 305.0629 310.1281 Zipf 0.11033 -0.74705 61.0465 340.9567 346.0219 Mande...

...oldpin)) > plot(1,1) > } > > windows(5,3) > > par(pty="s") > plot(1,1) > # square > par(pty="m") > plot(1,1) > > # which settings do we have before > par1 <- par() > > somefunc() > > # which settings do we have now > par2 <- par() > # do they differ: yes on plt > all.equal(par1, par2) > > # reset plt > par(plt=par1$plt) > > # which settings do we have now > par2 <- par() > # do they differ: no > all.equal(par1, par2) > > par(pty="s") > plot(1,1) > #still n...

...simulation runs. I need to calculate the root mean squared error. For each estimate I extract the corresponding parameter value from the column name of the estimates: rmse <- function(est){ parname <- deparse(substitute(est)) par1 <- unlist(strsplit(parname, c("\\.")))[1] par2 <- eval(parse(text=par1)) sqrt(sum((par2- est)^2) /length(est)) } This works well for subsets (i.e. given parameter combinations), but not inside the summaryBy function because I cannot index properly. data1 <- subset(mydata, X==1) rmse(data1$b0.m1) summaryBy(b0.m5 X, data=mydata, FUN=c(...

Dear R-developer, Just some more details on the problem I reported several minutes ago. On an NT machine (4.0 SP6) I got the following for the same task: > version _ platform i386-pc-mingw32 arch x86 os Win32 system x86, Win32 status major 1 minor 2.0 year 2000 month