similar to: save conditions in a list

Hi I would like to have something like str <- "df$JT == 12" fun <- function(df) { b <- eval(parse(str)) return(b) } but for performance "eval(parse(a))" should not be evaluated at each function call, but should work as fun <- function(df) { b <- df$JT == 12 return(b) } Do you have an idea how I can implement this? Thx Christof

Hi is there a automatic way that long distances between points are not connected. I have something like plot(x,y,type="o",...) atx <- seq(as.Date("2009-04-01"),as.Date("2011-04-01"),"month") axis.Date(1, at=atx,labels=format(atx, "%b\n%Y"), padj=0.5 ) but I do not want lines between points whose distance is greater than two weeks. thx

Hi there are some predefined self-start functions, like SSmicmen, SSbiexp, SSasymp, SSasympOff, SSasympOrig, SSgompertz, SSflp, SSlogis, SSweibull, Quadratic, Qubic, SSexp (nlrwr) Btw, do you know graphic examples for this functions? The SSexpDecay (exponential decay) for y = (y0 - plateau)*exp(-k*x) + plateau from

Hi xyplot(y ~ x | subject) plots a separate graph of y against x for each level of subject. But I would like to have an own function for each level. Something like xyplot(y ~ x | subject, panel = function(x,y) { panel.xyplot(x,y) panel.curve(x,y) { # something that dependents on the current subject ... } }) How I get the current

Hi I like to use "axis.POSIXct" to plot days from 2006 till 2008. But I only have datas for the summer months. Is it possible to get two axis breaks, to have not so long distances without points? thx Christof

Hi one col in my Excel file contains many numbers. But on line 3000 and some other lines are strings like "FG 1". "RODBS" seems to omit this lines. "gdata" works, but is much slower. Is this a bug of RODBC or do I apply it wrong? Example with the same "file.xlsx" library(RODBC); excel <- odbcConnectExcel2007("file.xlsx") tab <-

Hi I would like to shorten mod1 <- nls(ColName2 ~ ColName1, data = table, ...) mod2 <- nls(ColName3 ~ ColName1, data = table, ...) mod3 <- nls(ColName4 ~ ColName1, data = table, ...) ... is there something like cols = c(ColName2,ColName3,ColName4,...) for i in ... mod[i-1] <- nls(ColName[i] ~ ColName1, data = table, ...) I am looking forward to help Christof

Hi, a have some code like myfunc <- function(x) { ...; return c(a,b) } ys <- sapply(0:100,myfunc) so I get something like c(c(a1,b1),c(a2,b2),...) But now I need the "as" and "bs" in one vector as <- apply(ys, function(c(a,b)) a) bs <- apply(ys, function(c(a,b)) b) Can you help me with the correct syntax, instead of my pseudo code? thx Christof

Hi I want to add a row to a "data.table" in each round of a for loop. "rbind" seems to be a inefficient way to implement this. How would you do this? The "slow" solution: library(data.table) Rprof("test.out") dt <- data.table() for (i in (1:10000)) { # algorithm that generates a list with different values, # but same key-names, each round, for

Hi, I want to fit nonlinear dose-response curves, as "fun(X,a,b,c)", for each of our 5 trail locations. Our data basis is something like location plot year dose response For each location there are 4 plots as repetitions (over 3 years). So the interactions "location*year" and "location*plot" should be random effects. There are some examples in "Mixed-Effects

Hi I have "observations" obs <- (11455, 11536, 11582, 11825, 11900, ...) and a simulation function f(A,B,C,D,E,F), so sim <- f(A,B,C,D,E,F) e.g. sim = c(11464, 11554, 11603, 11831, 11907, ...) now I would like to fit A,B,C,D,E,F such that "obs" and f(A,B,C,D,E,F) match as well as possible. A,..,F should be integers and have bounds. How would you solve this problem

Hi I want to do something like a <- c(10,20,15,43,76,41,25,46) tab <- data.frame(a) name <- "a" for (v in unique(tab[[name]])) { r <- subset(tab, name==v) # this does not work ... } i.e. a "string" on the left side of the select expression (subset). How could I solve this? thx Christof

Hi, mod <- lme(A ~ -1 + B+C+D+E+F+G, random = ~1 | ...) results in summary(mod)$coeff B C D E F G (Intercept) b c d e f g i Now I'm interested in the function f <- function(B,C,D,E,F,G) <- { return(i + b*B + c*C + d*D + e*E + f*F + g*G) } Is there a easier way to create such function with flexible number of coefficient, than do it by hand? thx Christof

Hi, I want to plot with axis.Date(), but something is scaled incorrectly. The red vertical line in is put on a totally wrong position. (sample below) Do you have an idea what I'm doing wrong? Thx Christof x11(width=30, height=20) x<-seq(as.Date("2010-02-27"), as.Date("2011-03-28"),"month") y <- seq(0,100,length=length(x)) plot(y ~ x,

Hi there are some good tips in "The R Inferno" http://www.burns-stat.com/documents/books/the-r-inferno/ or connect C++ to R with Rcpp http://dirk.eddelbuettel.com/code/rcpp.html or byte code compiler (library(compiler)) or library(data.table) but do you have an idea to fasten standard R source code, with the following Rprof output self.time self.pct total.time

Hello Everybody, I'm working with a dataframe that has 18 columns. I would like to subset the data in one of these columns, "present", according to combinations of data in six of the other columns within the data frame and then save this into a text file. The columns I would like to use to subset "present" are: * answer (1:4) [answer takes the values 1 to 4] *p.num

I might have factored the gender. I'm not sure it would in any way be quicker. But might be to some extent easier to develop variations of. And is sort of what factors should be doing... # make dummy data gender <- c("Male", "Female", "Male", "Female") WC <- c(70,60,75,65) TG <- c(0.9, 1.1, 1.2, 1.0) myDf <- data.frame( gender, WC, TG ) #

Hi, I am trying to extract subset of data from my original data frame based on some condition. For example : (mydf -original data frame, submydf - subset dada frame) >submydf = subset(mydf, a > 1 & b <= a), here column a contains values ranging from 0.01 to 100000. I want to extract only those matching condition 1 i.e a > . But when i execute this command it is

There are many techniques Callum and yours is an interesting twist I had not considered. Yes, you can specify what integer a factor uses to represent things but not what I meant. Of course your trick does not work for some other forms of data like real numbers in double format. There is a cost to converting a column to a factor that is recouped best if it speeds things up multiple times. The

Just a minor point in the suggested solution: df$LAP <- with(df, ifelse(G=='male', (WC-65)*TG, (WC-58)*TG)) since WC and TG are not conditional, would this be a slight improvement? df$LAP <- with(df, TG*(WC - ifelse(G=='male', 65, 58))) -----Original Message----- From: R-help <r-help-bounces at r-project.org> On Behalf Of Jorgen Harmse via R-help Sent: Friday,