similar to: help with e+01 number abbreviations

Dear ReXperts, I have the below text file output. I need to extract the T, QC, QO, QO-QC and WT columns for the data between T = 10 and T=150. Any ideas? Thanks in advance. ======================================================================================== 1 D C ---CAT-- T THETA QC QO QO-QC QC/QO WT FSD 8 1 0 1.0000E+01

Folks, Updating values in a table is simple in SAS or SQL, but I've wracked my brain looking for an elegant solution in R to no avail thus far. Certainly this is a common need that's been solved in dozens of different ways. Given an initial dataframe nn and a smaller dataframe of updates uu, I'd like to replace the values in nn <- expand.grid('a'=1:4, 'b'=1:3)

Hello RHelpers, This may already have been answered, but despite days of scouring through the archives I haven't found it. My goal is to add multiple fitted curves to a plot. An example data set (a data frame named df in following code) is: x1 y1 factor1 4 1298.25 0.00000000 1 5 1393.25 0.00000000 1 6 1471.50

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 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

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

Dear all, I was wondering if there is any way i could do a "Grid Search" on a parameter space using R (as SAS 6.12 and higher can do it) to start the Newton-Gauss Linearization least squares method when i have NO prior information about the parameter. W. N. Venables and B. D. Ripley (2002) "Modern Applied Statistics with S", 4 th ed., page 216-7 has a topic

Hi! I got a rather stupid question (I think): Is there ANY option that makes R display numericals not like "1e-8" but as "0.00000001" by default ? And I need the outcome to be really numerical, so formatC(...) which produces a character or something like this won't be acceptable. Any help on this would be appreciated, thanx. Marc

Dear R Helpers, I try to write a small package that based on nlme however my code does not work. R always appears this message: Error in eval(expr, envir, enclos) : object "y" not found where y is the response variable. Please help me out! This is my code: require(nlme) AMPmixed<-function(y, x, S1=c("asymptotic","logistic"), random,data,

I was using the hist() function to create a frequency table of some network traffic data. The range in values is rather large, from 0 till just under 10e12. Calling hist(x, breaks=c(0,1000,1e6,1e9,1e12),plot=F,freq=T) causes hist() to return : $breaks [1] -1.0000e+05 1.0100e+05 1.1000e+06 1.0001e+09 1.0000e+12 Is this recalculation of the breaks by hist() intended? Maarten van Gelder.

(I tried to send this earlier, but it doesnt seem to have come through, due to problems on my system) Hola: Both cannot be correct: > m <- matrix(1:4, 2) > svd(m) $d [1] 5.4649857 0.3659662 $u [,1] [,2] [1,] -0.5760484 -0.8174156 [2,] -0.8174156 0.5760484 $v [,1] [,2] [1,] -0.4045536 0.9145143 [2,] -0.9145143 -0.4045536 > La.svd(m) $d [1]

Hi, I'm having a problem converting a Matlab program into R. The R code works almost all the time, but about 4% of the time R's optim function gets stuck on a local minimum whereas matlab's fminsearch function does not (or at least fminsearch finds a better minimum than optim). My understanding is that both functions default to Nelder-Mead optimization, but what's different about

Dear R-users >prob <- c(0.5,0.4,0.3,0.1,0.0) >cal <- prob * log(prob,base=2) >cal [1] -0.5000000 -0.5287712 -0.5210897 -0.3321928 NaN Is there any way to change NaN to zero ? I did come up with this by applying Ripley's relpy to my previous question cal <-prob*log(pmax(prob,0.00000001),base=2) Any suggestion ? Thank you Taka

The function 'pchisq' from the 'stats' library gives a wrong result if the argument equals exactly zero: # Upper tail of central 1-df chi^2 distribution > pchisq(1 , 1, ncp=0, lower.tail = F, log.p = FALSE) [1] 0.3173105 > pchisq(0.5 , 1, ncp=0, lower.tail = F, log.p = FALSE) [1] 0.4795001 > pchisq(0.01 , 1, ncp=0, lower.tail = F, log.p = FALSE) [1]

Dear all, I have a function that predicts DV based on one predictor pred: pred<-c(0,3000000,7800000,15600000,23400000,131200000) DV<-c(0,500,1000,1400,1700,1900) ## I define Function 1 that computes the predicted value based on pred values and parameters a and b: calc_DV_pred <- function(a,b) { DV_pred <- rep(0,(length(pred))) for(i in 1:length(DV_pred)){ DV_pred[i] <- a *

I am looking for a method of dealing with the modified Bessel function K_\nu(x) for large \nu. The besselK function implementation of this allows for dealing with large values of x by allowing for exponential scaling, but there is no facility for dealing with large \nu. What would work for me would be an lbesselK function in the manner of lgamma which returned the log of K_\nu(x) for large

Hi guys, I have a code in R and it was work well but when I decrease the epsilon value (indicated in the code) , then I am getting this error Error: evaluation nested too deeply: infinite recursion / options(expressions=)? any help please y = 6.8; w = 7.4; z = 5.7; muy = 7; muw = 7; muz = 6; sigmay = 0.8; sigmaz = 0.76; sigmaw = 0.3; betayx = 0.03; betayz = 0.3; betayw = 0.67 s =

Dear List, I have been trying to use p.adjust() to do BH multiple test correction and have gotten some unexpected results. I thought that the equation for this was: pBH = p*n/i where p is the original p value, n is the number of tests and i is the rank of the p value. However when I try and recreate the corrected p from my most significant value it does not match up to the one computed by the