similar to: interaction plot and x axis

Dear all, I want to make a plot where I can specify the range of y axis. I am using the interaction.plot command and because the values of y axis are from 2 to 500, I am using a logarithmic scale. >interaction.plot(speclong$Date,speclong$time2,speclong$outcome,xaxt="n",type="l",pch=20,xlab="", log="y", ylab="Concentration

Dear all, I want to plot 8 chemical variables in the same plot. I have used the interaction.plot command: > interaction.plot(speclong$Date,speclong$time2,speclong$outcome,xaxt="n",type="l",pch=20,xlab="", log="y", ylab="Concentration (ug/L)",trace.label="",col=rainbow(8)) However, what it gives me is dotted lines and the colours are

Hi, I am trying to find m breakpoints of a linear regression model. I used the segmented package. It works fine for small number of predicators and breakpoints.(3 r.v. 3 points). However, my model has 14 variables it even would not work even for just one breakpoints!. The error message is always estimated breakpoints are out of range. Since my problem is time related problem. So I

Dear List I want to plot multiple time series (several outcomes) with dates at intervals on the x axis and a legend. Is it possible to use axis.Date to get dates, at intervals in my case, on the x axis of a (multiple) time series plot. The axis.Date in the code below doesn't produce any dates on the x axis. (The difference outcome measures are all variable outcome in dataframe speclong and

Dear all I have the following code to produce a graph of 5 different variables in the same graph; however when I follow it in the end it produces the plot of the 5 variables and a legend in right but the problem is that the legend is too close to the margin of the plot and when I try to write the text for each line it does not fit. How can I change the location of the legend to be placed a little

Dear all, I am ploting two boxplot of two chemical variables using the format boxplot(Alkalinity, logAlkalinity, log="y", col=c("lightblue"), lwd=0.6, boxwex=0.3) However when I plot like this, the distance between the two boxplots is very big and as well the distance of each boxplot from the plot area, left and right. How can I minimise that distance between the boxplots and

Friday I enabled the inlinehint function attribute in the inliner. It mostly affects the performance of -Os compiled code. I have made some measurements on the SPEC test suite to show what it means. I made three runs of then nightly tests. The baseline represents -Os with no inlinehint: make TEST=nightly OPTFLAGS=-Os EXTRA_LOPT_OPTIONS=-inlinehint-threshold=0

Dear all, I want to do some time plots and actually the dates are in the format of dd/mm/yyyy. So first I input my dataframe in R in a csv form. What I do is DF<-read.csv("C:/Documents and Settings/DF.csv") DATE<-as.Date(DATE, "%d/%m/%Y") # to tell R that DATE column is indeed dates with(DF, plot(DATE,pH)) Until here it works fine, but I have the graph plotting

Full_Name: Suharto Anggono Version: 2.8.1 OS: Windows Submission from: (NULL) (125.165.84.118) PR#14076 inspired me to write this. > t1 <- as.POSIXct("1970-01-01 00:00:00", tz="GMT") > t2 <- as.POSIXlt("1970-01-01 00:00:00", tz="GMT") > t1 - t2 Time difference of 7 hours Above, t1 and t2 represent the same time in the same specified

Dear all, I am trying to make boxplots in one diagram but it is not working. Actually I have a large dataset, around 35 water quality variables with different units and of course in different ranges (some are orders of magnitude bigger than others). I want to produce one diagram with all the boxplots of the variables of my dataset. I tried these series of commands: >oldpar <-

Hi r users, I have two data sets (X1, X2). For example, time1<-c( 0, 8, 15, 22, 43, 64, 85, 106, 127, 148, 169, 190 ,211 ) outpue1<-c(171 ,164 ,150 ,141 ,109 , 73 , 47 ,26 ,15 ,12 ,6 ,2 ,1 ) X1<-cbind(time1,outpue1) time2<-c( 0 ,8 ,15 , 22 ,43 , 64 ,85 ,106 ,148) output2<-c( 5 ,5 ,4 ,5 ,5 ,4 ,1 ,2 , 1 ) X2<-cbind(time2,output2) I want to

Dear List, I have (for example) 50 observations collected from 50 experimental sites and want to look at changes of 50 observations as function of time in a graph. I found that I could do that using R-code below: time2 <- 1:25 y1=rnorm(25, mean=0, sd=1) y2=rnorm(25, mean=0, sd=1) ... y50=rnorm(25, mean=2, sd=1) plot(time2, y1, type='b', xlim=range(0,30), ylim=range(y1, y2),

Dear everyone, My question involves the use of the survival object. We can have Surv(time,time2,event, type=, origin = 0) (1) As detailed on p.65 of: http://cran.r-project.org/web/packages/survival/survival.pdf My data (used in my study) is 'right censored' i.e. my variable corresponding to 'event' indicates whether a person is alive (0) or dead (1) at date last seen

Hello List, I'm moving my asterisk testing installation from CENTOS 5.4 on a real machine to SUSE on a xen VM. Everything seemed to go off without a hitch until I really looked at it. The call answers and processes correctly, but when it is time to end the call, the phone never disconnects from asterisk. For a simple functionality test, I use this "Monkeys"

Greetings listeRs - Given a data frame such as times time1 time2 time3 time4 1 70.408543 48.92378 7.399605 95.93050 2 17.231940 27.48530 82.962916 10.20619 3 20.279220 10.33575 66.209290 30.71846 4 NA 53.31993 12.398237 35.65782 5 9.295965 NA 48.929201 NA 6 63.966518 42.16304 1.777342 NA one can use "transform" to

Further pursuing my curiosity to measure the efficiency of R/C++ interface, I conducted a simple matrix-vector multiplication test using .C and .Call functions in R. In each case, I measured the execution time in R, as well as inside the C++ function. Subtracting the two, I came up with a measure of overhead associated with each call. I assume that this overhead would be non-existent of the entire

Hi, I would like to merge two data frames. It is just that I want the merging to be done with some kind of a fuzzy criterion. Let me explain. My first data frame looks like this : ID1 time1 dt 1 2008-01-02 13:11 10 2 2008-01-02 14:20 20 3

Hello. I get a bit confused by the output from the predict function when used on an object from coxph in combination with p-spline, e.g. fit <- coxph(Surv(time1, time2, status)~pspline(x), Data) predict(fit, newdata=data.frame(x=1:2)) It seems like the output is somewhat independent of the x-values to predict at. For example x=1:2 gives the same result as x=21:22. Does the result span the

Dear All,   #I have the following code   Dose<-1000 Tinf <-0.5 INTERVAL <-8 TIME8 <-matrix(c((0*INTERVAL):(1*INTERVAL))) TIME7 <-matrix(c((0*INTERVAL):(2*INTERVAL))) TIME6 <-matrix(c((0*INTERVAL):(3*INTERVAL))) TIME5 <-matrix(c((0*INTERVAL):(4*INTERVAL))) TIME4 <-matrix(c((0*INTERVAL):(5*INTERVAL))) TIME3 <-matrix(c((0*INTERVAL):(6*INTERVAL))) TIME2

To Whomever is Interested, I have spent several days searching the web, help files, the R wiki and the archives of this mailing list for a solution to this problem, but nonetheless I apologize in advance if I have missed something obvious. The problem is this; I have a 5-column data frame with about 4.2 million rows, and want to create a new (and hopefully much smaller) data frame that