similar to: Data extraction

Dear all: I attached the dataset with this email and post codes as below. My questions is related to the 'col=temp.col' for the line and pch in my code, I have 4 IDs, 10 DIDs and each ID include different DIDs, for example, first ID has 3 DIDs, then the color is the first three colors(black, red, green) in the first plot, but in the second plot, why the color change to pink which is

System info: Linux slackware R Version 1.5.1 (2002-06-17) ESS 5.1.21 Emacs 21.2.1 ------------------- Colleagues I have some text files in a certain directory and want to process them sequentially. So I want to pass the filename identifier into a function and loop through the processing of each file in turn.I've called the file identifier f in this code segment: image.dvm <- function

Dear List, I will appreciate any advice regarding how to convert the following numbers [I got in return by taxondive()] in numeric integers without the e.g. 6.4836e+01 abbreviations. Thank you very much in advance, Gian > taxa_dive Species Delta Delta* Lambda+ Delta+ S Delta+ Nat1 5.0000e+00 6.4836e+01 9.5412e+01 6.7753e+02 8.7398e+01 436.99 Nat2

R 2.15.1 OS X and Windows Colleagues, I have a file that looks that this: TABLE NO. 1 PTID TIME AMT FORM PERIOD IPRED CWRES EVID CP PRED RES WRES 2.0010E+03 3.9375E-01 5.0000E+03 2.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 1.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 0.0000E+00 2.0010E+03 8.9583E-01

Dear all: I have been thinking to import below one data file (.txt)into R by read.table(..,skip=1, header=T). But How can I deal with the repeated rows of TABLE NO.1 and names of data variables in the middle of this data file. The similar block will be repeated 100 times, here only show 4 of them and within each block, data records also can vary, here only paste 4 rows for example. I appreciate

Dear all: I have been thinking to import below one data file (.txt)into R by read.table(..,skip=1, header=T). But How can I deal with the repeated rows of TABLE NO.1 and names of data variables in the middle of this data file. The similar block will be repeated 100 times, here only show 4 of them and within each block, data records also can vary, here only paste 4 rows for example. I appreciate

R 2.15.1 OS X Colleagues, I am reading a 1 GB file into R using read.table. The file consists of 100 tables, each of which is headed by two lines of characters. The first of these lines is: TABLE NO. 1 The second is a list of column headers. For example: TABLE NO. 1 COL1 COL2 COL3 COL4 COL5 COL6 COL7 COL8 COL9 COL10

Dear Rxperts, I have the following data: Study Study.Name C Category TC Time QC QO SD FSD Theta 1 NONE 0 P(22) 0 0.00 7.5596 0 0 8.0361e-03 0 1 NONE 6 G(50) 0 0.00 1.0000 0 0 0.0000e+00 0 1 NONE 2 F(02) 0 0.00 100.0000 0 0 0.0000e+00 0 1 NONE 3 F(03) 0 0.00 13.2280 0 0 1.6732e-02 0

Hi, I'm estimating a loglogistic aft (accelerated failure time) model, just a simple plain vanilla one (without time dependent covariates), I'm comparing the results that I obtain between aftreg (eha package) and survreg(surv package). If I don't use any covariate the results are identical , if I add covariates all the coefficients are the same until a precision of 10^4 or 10^-5 except

Should I submit this as a bug report? --- reg-tests-3.Rout.save Thu Jul 3 09:55:40 2003 +++ reg-tests-3.Rout Sun Nov 23 13:10:57 2003 @@ -1,17 +1,18 @@ -R : Copyright 2003, The R Development Core Team -Version 1.8.0 Under development (unstable) (2003-07-03) +R : Copyright 2003, The R Foundation for Statistical Computing +Version 1.8.1 (2003-11-21), ISBN 3-900051-00-3 R is free software and

>> I have come across your reported log1p error (#2837) on a NetBSD (1.6W) >> system. I've just made further experiments on the deficient log1p() function on OpenBSD 3.2 and NetBSD 1.6 with this test program: % cat bug-log1p.c #include <stdio.h> #include <stdlib.h> #include <math.h> int main(int argc, char* argv[]) { int k; double x; for (k = 0; k

Dear Wiza[R]ds, I have the following data in a data.frame. I need to do an anova with multiple comparison but I don't know how to factor the groups for analysis. There are 3 groups, 1,2 and 3 labelled in column 1. Help appreciated with thanks in advance. Group SI Sif SG Io I2 lol2 1 9.08e-05 9.08e+00 0.060842287 1.798556446 32.574500

Upgrading an ancient customer installation... was running 1.4.23.1 (Trixbox) with Zaptel 1.4.12.9 and a Sangoma A102D, which has been running fine for 5+ years. Customer getting anxious about hardware failure, so we built a new box and installed 1.8.24.0, Dahdi 2.7.0.1, and a new Sangoma A104D. The single active span is an RBS T1 B8ZS/ESF/E&M Wink. I tried to move one span over one

Hello, Are there any R functions available for performing a serial correlation test for short time series (e.g, series having between 10-14 observations)? Many thanks! Isabella R. Ghement, Ph.D. Ghement Statistical Consulting Company 301-7031 Blundell Road, Richmond, B.C., Canada, V6Y 1J5 Tel: 604-767-1250 Fax: 604-270-3922 E-mail: isabella at ghement.ca Web: www.ghement.ca -----Original

Greetings, I implemented BRugs to run the EWOC model with a cohort size N=1. I output the simulation data using bugsdata(data), where data is the following list. > data $Dose [1] 140 $Y [1] 0 bugsdata(data) puts out the file data.txt as follows. list(Dose=1.40000E+02, Y=0.00000E+00) after I type the following line modelData("data.txt")

dear R users, the data frame (read in from a csv) looks like this: TreeTag Census Stage DBH 1 CW-W740 2001 juvenile 5.8 2 CW-W739 2001 juvenile 4.3 3 CW-W738 2001 juvenile 4.7 4 CW-W737 2001 juvenile 5.4 5 CW-W736 2001 juvenile 7.4 6 CW-W735 2001 juvenile 5.4 ... 1501 1.00E-20 2001 adult 32.5 i would like to

Hi all, I am trying to run Weibull PH model in R. Assume in the data set I have x1 a continuous variable and x2 a categorical variable with two classes (0= sick and 1= healthy). I fit the model in the following way. Test=survreg(Surv(time,cens)~ x1+x2,dist="weibull") My questions are 1. Is it Weibull PH model or Weibull AFT model? Call: survreg(formula = Surv(time, delta) ~ x1

Hello, We use drc to fit dose-response curves, recently we discovered that there are quite different standard error values returned for the same dataset depending on the drc-version / R-version that was used (not clear which factor is important) On R 2.9.0 using drc_1.6-3 we get an IC50 of 1.27447 and a standard error on the IC50 of 0.43540 Whereas on R 2.7.0 using drc_1.4-2 the IC50 is

I have a data-set that is structured as follows: sp wg n v.realtime v.cputime v.tcputime v.idletime v.nswtch 9 0 1 1 28.61300 28.61 28.6039 0.00000e+00 407 1563 0 1 2 15.20270 30.38 28.5981 9.80523e-01 483 3128 0 1 4 12.50930 50.00 28.6053 1.07877e+01 489 4682 0 1 6 12.10260 72.55

Dear R-list users, I'm new to principal components and factor analysis. I thought this method can be very useful for me to find relationships between several variables (which I know there is, only don't know which variables exactly and what kind of relation), so as a structure detection method. Now, I'm experimenting with the function prcomp from the mva package. In my source code