similar to: visualize lme results

I'm trying to use plotting character to encode the variable "block" from my dataset in a conditioned lattice graphic (R 1.9.0 on Mac OS 10.3.3). The data I'm using is the dataframe "dryoutcover" which is here (4k): http://anthony.darrouzet-nardi.net/downloads/dryoutcover.Rdata The code that generates my graphic almost correctly is as follows: xyplot(coversage ~

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

I am so happy about learning how to read in multiple Excel files, that I have to try and make another improvement. I know what I have been doing is clumsy, but it works. Hopefully, someone can suggest a more elegant solution. As a novice, I have been using MS-Word and mail merge to write my code. I start with about 2 pages of code, and end up with 2,220 merged pages that I copy and paste into R.

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, 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 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

I have a script that draws 9 graphics which I would like to run by source()ing the file. In the script I make objects that contain each of the graphics (all lattice objects or functions that contain lattice functions). Then at the end of the script, I have a section which prints them to separate eps files like this: postscript(file = "dryoutcover.eps", height = 5, width = 7,

I've been trying to get RODBC working in RAqua. For my database, let's call it "mydb", when I enter odbcConnect("mydb") or odbcConnect("mydb", uid="postgres", pwd="secret"), RAqua thinks for about 10 seconds, then crashes. mydb is a PostgreSQL 7.4.2 database running on my machine (Mac OS X 10.3.3). I am using the pgsqlodbc 7.2.5 driver

I've been trying to setup AddQueueMember() as a replacement for the deprecated AgentCallbackLogin(), but I get _tree_ Queue()'s. Massaged extensions.conf (can provide the original if need be): ----- s n i p ----- [default] include => agent-loginout include => local ; ---------- [agent-loginout] exten => _100.,n,Macro(queue-addremove,I${EXTEN:3},dispatch,10)

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 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 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 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 have a vector, which contains both strings and numbers, e.g. > foo <- c("str1",1234,"str2",0.9876) I want to know if a distinct element of the vector is a string or a number and took "is.numeric", but > is.numeric(foo[2]) [1] FALSE because R treats the numbers in a mixed vectors as strings: > foo [1] "str1" "1234"

Hi, I have a dataframe (say myData) and want to get a list (say myList) that contains a matrix for each row of the dataframe myData. These matrices are calculated based on the corresponding row of myData. Using a for()-loop to do this is very slow. Thus, I tried to use apply(). However, afaik apply() does only return a list if the matrices have different dimensions, while my matrices have

Hello to everyone, I have 2 problems and would be very pleased if anyone can help me: 1) When I use the package "systemfit" for SUR regressions, I get two different variance-covariance matrices when I firstly do the SUR regression ("The covariance matrix of the residuals used for estimation") and secondly do the OLS regressions. In the manual for "systemfit" on page