similar to: selection part of "subset"

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 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 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 how would you save conditions like a = "day > 100"; b = "val < 50"; c = "year == 2012" in a list? I like to have variables like "day", "val", "year" and a list of conditions list(a,b,c). Then I want to check if a & b & c is true or if a | b | c is true or similar things. Greetings Christof

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, 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

Hi Christof! AFAIK, PowerDNS is the only open source name server that supports ALIAS. There was an idea to standardize ALIAS as "ANAME" (https://datatracker.ietf.org/doc/draft-ietf-dnsop-aname/), but the idea was dropped in favor of SVCB/HTTPS record https://datatracker.ietf.org/doc/rfc9460/. So now we have to wait until all Browser vendors implement SVCB/HTTPS. Regards Klaus PS: If

I'm trying to bring dovecot up on Debian/stable using Christof Meerwald's unofficial packages (cmeerw.org/debian/). This package seems to work fine on Debian/testing. There error I'm getting on the stable box is: gnutls_handshake: A TLS fatal alert has been received.(Bad record MAC) Any guesses? -- Jacob Elder

Hi Andy, Andrew Trick wrote: >> On Sep 23, 2016, at 7:50 AM, Christof Douma <Christof.Douma at arm.com <mailto:Christof.Douma at arm.com>> wrote: >> >> I can’t help to ask. Why not define a wrapping nsw instruction as UB, instead of “delayed UB” aka poison? I believe we >> have the notion of poison solely to ease the movement of instructions. In my example

Hi, I have a dataframe containing data from individuals 1, ..., 12 (grouping variable "g" in the data frame below), which belong either to "A" or "B" (grouping variable "f"): set.seed(1) tmp <- data.frame(

Hi R-helpers I have a dataframe DF (lets say with the variables, y, x1, x2, x3, ..., clust) containing relatively many NAs. When I fit an ordinal regression model with the function lrm from the Design library: model.lrm <- lrm(y ~ x1 + x2, data=DF, x=TRUE, y=TRUE) it will by default delete missing values in the variables y, x1, x2. Based on model.lrm, I want to apply the robust covariance