search for: thedata

...below. Many thanks, Andy ################################################################# require(lme4) # First generate some data people = 100 obs = 4 # The random intercepts: sub_noise = data.frame(id = 1:people, rand_int = rnorm(people,0,60)) # Merge everything id = rep(1:people,obs) thedata = data.frame(id) thedata = merge(sub_noise, thedata) thedata$x = rep(1:obs,people) # Setup the relationship between x and y thedata$y = 23*thedata$x + 20 + thedata$rand_int + rnorm(people*obs, 0, 20) # plus residuals # Have a look plot(y~x, data = thedata) # Now fit a standard r...

...e hundreds of megabytes of price data time series, and perl scripts that extract it to tab delimited files (I have C++ programs that must analyse this data too, so I get Perl to extract it rather than have multiple connections to the DB). I can read the data into an R object without any problems. thedata = read.csv("K:\\Work\\SignalTest\\BP.csv", sep = "\t", header = FALSE, na.strings="") thedata The above statements give me precisely what I expect. The last few lines of output are: 8190 2009-06-16 49.30 8191 2009-06-17 48.40 8192 2009-06-18 47.72 8193 2009-06-19 48....

...require(lme4) set.seed(0) # Data for 100 people, each of whom has 10 observations people = 100 obs = 10 # Generate person-level variation sub_noise = data.frame(id = 1:people, rand_int = rnorm(people,0,60)) # And within person noise resids = rnorm(people*obs, 0, 20) id = rep(1:people,obs) thedata = data.frame(id) thedata = merge(sub_noise, thedata) thedata$x = rep(1:obs,people) thedata$y = 23*thedata$x + 20 + thedata$rand_int + resids thedata$y.flat = 23*thedata$x + 20 + resids # Fit a random intercept model lmer1 = lmer(y ~ x + (1|id), data=thedata) summary(lmer1) # Get the intercepts...

Hi, A simple question I hope. I wish to add a single vertical line to a plot with several density plots. Here is a simplified example. ############ thedata <- data.frame(x1=rnorm(100,1,1),x2=rnorm(100,3,1)) #create data thedata.m<-melt(thedata) densityplot(~value, thedata.m, groups=variable,auto.key=list(columns=2)) #this gives the two density plots ######### what I wish now is to add a vertical line, for example v=2. Many thanks, Josh. [[al...

...s a set of variables exported from Octave 'x y tri xiflat yiflat tri_list.mat' https://pastebin.com/xELkj6r6 the variable tri_list is just the tri_list = search(x,y,tri_deldir,xiflat,yiflat) in Octave The command history is a as follows: library(deldir) library(geometry) library(foreign) theData <- read.octave('x y tri xiflat yiflat tri_list.mat') options(digits = 10) x <- unlist(theData[1]) y <- unlist(theData[3]) tri_deldir <- triMat(deldir(x,y)) tri_delaunayn <- delaunayn(x,y) tri_delaunayn <- delaunayn(cbind(x,y)) tri_list_from_deldir <- tsearch(x,y,tri_del...

...quot;,"15:06",0.000000 ...etc... I am trying to make a plot of 'X' vs. 't' where 'x' is a simple numerical vector of N elemets and 't' is a timestamp like "mm/dd/yyyy hh:mm:ss" (also of N elements) here is how i am getting the data: > >TheData <- scan("MyDataFile.txt",sep=",",list("","",0)) >TheDates <- TheData[[1]] >TheTimes <- TheData[[2]] >TheValue <- TheData[[3]] > and here is how i am making the datetime objects: > >TimeStampStr <- paste(TheDates,TheTimes...

...t doesn't already? mpirun -np 4 -machinefile /var/spool/PBS/aux/90361.head /apps/R/R270/bin/R CMD BATCH --save Rmpi_test4.R # Initialize MPI library("Rmpi") # Function the slaves will call to perform a validation on the # fold equal to their slave number. # Assumes: thedata,fold,foldNumber,p foldslave <- function() { # Note the use of the tag for sent messages: # 1=ready_for_task, 2=done_task, 3=exiting # Note the use of the tag for received messages: # 1=task, 2=done_tasks junk <- 0 done <- 0 while (done !...

...close.Rslaves() to close slaves.") mpi.close.Rslaves() } print("Please use mpi.quit() to quit R") .Call("mpi_finalize") } } # Function the slaves will call to perform a validation on the # fold equal to their slave number. # Assumes: thedata,fold,foldNumber,p foldslave <- function() { # Note the use of the tag for sent messages: # 1=ready_for_task, 2=done_task, 3=exiting # Note the use of the tag for received messages: # 1=task, 2=done_tasks junk <- 0 done <- 0 while (done != 1) { #...

...'m very confident that this equation is working properly. I would expect the outputs of this function to be roughly equivalent to the results from object "p" as seen above, but they don't look similar at all. I'm not sure what this means. tBLparamsForOneSpecies <- function(theData) { x <- theData[ ,1] y <- theData[ ,2] logitReg <- glm(y ~ x + I(x^2), family=binomial) b0 <- logitReg$coefficients[1] b1 <- logitReg$coefficients[2] b2 <- logitReg$coefficients[3] opt <- (-b1)/(2*b2) tol <- 1 / sqrt(-2*b2) pmax<-1/(1+exp(b1^2/(4*b2)-b0)) thePar...

Hello, On Mac OS X, certain Aqua/Quartz UI functionality requires an application to be launched from within an app bundle, or (alternatively) requires a Carbon application with a resource fork. Playing with the wxWidgets distribution, I discovered that it is quite easy and transparent to make such a Carbon app from (I guess) any command line application. When applied to the R executable called

Hello, On Mac OS X, certain Aqua/Quartz UI functionality requires an application to be launched from within an app bundle, or (alternatively) requires a Carbon application with a resource fork. Playing with the wxWidgets distribution, I discovered that it is quite easy and transparent to make such a Carbon app from (I guess) any command line application. When applied to the R executable called

Hi all, I'm handling massive data.frames and matrices in R (30000 x 400). In the 1st column, say, I have 0s and 1s indicating rows that matter; other columns have probability values. One simple task I would like to do would be to get the column mean values for signaled rows (the ones with 1) As a very fresh "programmer" I have build a simple function in R which should not be very

...ri xiflat yiflat tri_list.mat' > https://pastebin.com/xELkj6r6 > > the variable tri_list is just the tri_list = search(x,y,tri_deldir,xiflat,yiflat) > in Octave > > > The command history is a as follows: > library(deldir) > library(geometry) > library(foreign) > theData <- read.octave('x y tri xiflat yiflat tri_list.mat') > options(digits = 10) > x <- unlist(theData[1]) > y <- unlist(theData[3]) > tri_deldir <- triMat(deldir(x,y)) > tri_delaunayn <- delaunayn(x,y) > tri_delaunayn <- delaunayn(cbind(x,y)) > tri_list_fr...

...a1 <- 0.2 # event rate in group 1 t0 <- 10 # time to estimate expected numbers of events # 'correct' number of events at time t0 = rate of events (lambda) times time (t0) t0*lambda0 t0*lambda1 # generate uncensored data T0 <- rexp(nn, rate=lambda0) T1 <- rexp(nn, rate=lambda1) thedata <- data.frame(Time=c(T0, T1), X=rep(0:1, e=nn), X2=rep(0:1, nn)) # 4 covariate combinations (ndf <- data.frame(Time=t0, X=rep(0:1,e=2), X2=rep(0:1, 2))) # model with 2 effects mod <- coxph(Surv(Time) ~ X + X2, data=thedata) summary(mod) # coefficient of X2 should be 0 # coefficient of X...

...uestion is on scripting basics). For purposes of figuring out my needs, lets just consider writing a function that takes a formula and a dataset, and outputs the mean of each variable in the formula model. So: MyFunction <- function(AFormula, ADataFrame) { ... } >MyFunction(Y ~ A + B, TheData) would give results something like: Mean of MyData$Y is 5.3 Mean of MyData$A is 3.4 Mean of MyData$B is 8.2 QUESTION 1: How do I determine the terms in the formula within the function? QUESTION 2: How do I use one of those terms to get to the individual columns, like MyData$Y ? Thanks! -E...

I am trying to plot multiple densityplots on each panel, and using panel.groups to do some additional plotting (not included in the example) as in this example. library(lattice) thedata <- data.frame(x=rnorm(1200),class=rep(1:3,each=200,times=2), group=rep(1:2,each=100,times=6)) densityplot(~x | class,groups=group, xlab='x', panel.groups = function(x,subscripts,groups,panel.number,...) { panel.densityplot(x=x,subscripts=subscripts,groups=groups,...) # other stuff...

Hi Usually "aggregate" is used to calculate things such as the sum of all data on the first day, the sum next day, and so on. But how can I calculate the mean of the first hour of all days, the mean of the second hour of all days, and so on. ??? That's Most examples: today at 1am + today at 2am + today at 3am +.... -> sum today tomorrow at 1am + tomorrow at

...ri xiflat yiflat tri_list.mat' > https://pastebin.com/xELkj6r6 > > the variable tri_list is just the tri_list = search(x,y,tri_deldir,xiflat,yiflat) > in Octave > > > The command history is a as follows: > library(deldir) > library(geometry) > library(foreign) > theData <- read.octave('x y tri xiflat yiflat tri_list.mat') > options(digits = 10) > x <- unlist(theData[1]) > y <- unlist(theData[3]) > tri_deldir <- triMat(deldir(x,y)) > tri_delaunayn <- delaunayn(x,y) > tri_delaunayn <- delaunayn(cbind(x,y)) > tri_list_fr...

...s[j].nodeType != 1) continue try { //this.sdEventInfo[ei[0].childNodes[j].nodeName] = ei[0].childNodes[j].firstChild.nodeValue; //this.options.sdEventInfo.push(ei[0].childNodes[j].firstChild.nodeValue ); var theData = ei[0].childNodes[j].firstChild.nodeValue; } catch (e) { var theData = " "; $(''debug'').innerHTML += e+"<br />"; //th...

Hello, I have a data frame with 1425 observations, 539 of which are zeros. I am trying to fit the following ZINB: f3<-formula(Nbr_Abs~ Zone * Year + Source) ZINB2<-zeroinfl(f3, dist="negbin", link= "logit", data=TheData, offset=log(trans.area), trace=TRUE) Zone is a factor with 4 levels, Year a factor with 27 levels, and Source a factor with 3 levels. Nbr_Abs is counts of a species that shows a high level of aggregation. These counts are offset by the area searched per transect. The trace output and error messag...