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Dear all, I am quite new to R; facing certain problems: Say, I have a text file( named as "try"): Year C1 C2 C3 C4 C5 C6 Y1 3.5 13.8 9.5 6.8 0.4 24.2 Y2 3.8 13.9 9.9 7.6 0.7 12.8 Y3 4.5 14.5 14.2 9.2 0.6 14.5 Y4 5.9 16.2 24.6 12.7 0.2 24.3 Y5 7.2 20.4 40.6 18.2 0.8 28.2 Y6 5.9 18.6 37.4 14.5 0.3 36.9 Y7 8.0 16.1 88.6 24.1 0.1 34.6 Y8 13.6 21.1 56.3 19.0 0.7 33.3 I wish to import the

I have timstamped data like this: > sd[1:10,] Tstamp Density Mesh50 Mesh70 Mesh100 Mesh150 Mesh200 2 2009/02/27 07:00 30.5 0.7 10.7 21.4 32.8 41.6 3 2009/02/27 08:00 32.2 1.6 12.4 23.3 34.5 43.0 4 2009/02/27 09:00 32.7 4.8 13.0 24.0 35.1 43.5 5 2009/02/27 10:00 26.7 0.3 6.5 17.6 28.1 36.9 6 2009/02/27 11:00

Hi all, I have a dataframe (df1) that I am trying to select values from to a second dataframe that at the current time is only for the selected items from df1 (df2). The values that I am trying to save from df1 are factors with alphanumeric names df1 looks like this: 'data.frame': 3014 obs. of 13 variables: $ Num : int 1 1 1 2 2 2 3 3 3 4 ... $ Tag_Num : int 1195

Dear helpers I constructed a data frame with this structure > str(dados1) `data.frame': 485 obs. of 16 variables: $ Emissor : int 1 1 1 1 1 1 1 1 1 1 ... $ Marisca.Rio : int 1 1 1 1 1 1 1 1 1 1 ... $ Per?odo : int 1 1 1 1 1 1 1 1 1 1 ... $ Reproducao : int 3 3 3 3 3 3 3 3 3 3 ... $ Estacao : int 2 2 2 2 2 2 2 2 2 2 ... $ X30cm : int

Hi R-users, I have missing data for the month. My question is how do I insert the missing month and fill up the cell with 'na' for the rain amount?  Then I would like to count the percentage of missing data. No     Year     month rain 1398 1985    10 104.2 1399 1985    11 138.0 1400 1985    12 120.4 1401 1986     1  12.6 1402 1986     2  19.4 1403 1986     3   1.0 1404 1986     4  58.8

I am working with a longitudinal data set in the long format. This data set has three observations per grade level per year. Here are the first 10 rows of the data frame: >tenn.dat[1:10,] year schid type grade gain se new cohort 6 2001 100005 5 4 33.1 3.5 4 3 7 2002 100005 5 4 33.9 3.9 4 2 8 2003 100005 5 4 32.3 4.2 4 1 10 2001 100005

Hi, I have browsed the help list and looked at the FAQ but I don't find conclusive evidence if this is normal or I am doing something wrong. I am running a lm() on a data.frame with 27136 observations of 6 variables (3 num and 3 factor). After a while R throws this: > lm(log(y) ~ log(a) + log(b) + c + d + e, data=reg.data , na.action=na.exclude) Error: cannot allocate vector of size

Hi, If I set the p.adjust="none", does it meant that the output p values from the pairwise.t.test will be the same as those from individual t.tests (set var.equal=T, alternative="t")? I actually got different p values from the two tests. See below. Is it supposed to be this way? Thanks Johnny > x [1] 61.6 52.7 61.3 65.2 62.8 63.7 64.8 58.7 44.9 57.0 64.3 55.1 50.0 41.0

Hi I have a dataset which is like this: ID X1 Y1 Z1 X2 Y2 Z2 1 32 127 85 31.7 121 85 2 37.9 153 88 34.6 137 90 3 36.8 134 88 36.1 155 97 4 31.4 136 87 29 113 70 I would like draw the arrow or segment line for each ID from (x1, y1, z1) to (x2, y2, z2) Is there a way to do this kind of 3-D graph. Thank you -- View this message in context:

I have a problem. My data is now in this form: plot area d 1 0.01 34.6 ................... 100 0.01 15.7 First, I want to aggregate plots start from a plot in the center of sample (10 plots x 10 plots). I want to aggregate after the model plot1 in the center of area (0,01 m2), after increasing plot area with the near plots until the entire area (10000 m2). For a good explication I will

Hi, I have a financial (zoo) time series with prices and volumes (although I can get the coredata as a matrix). Due to the data-source some indices have multiple observations. I want to aggregate these according to a weighted average. 11:00:01 34 1000 11:00:01 35 500 11:00:01 35 1000 11:00:02 34 500 11:00:02 35 500 should become 11:00:01 34.6 2500 11:00:02 34.5 1000 I currently do this

Dear all, May I ask is there any functions in R to evaluate the fitness of "coxph" and "survreg" in survival analysis, please? For example, the results from Cox regression and Parametric survival analysis are shown below. Which method is prefered and how to see that / how to compare the methods? 1. coxph(formula = y ~ pspline(x1, df = 2))

Hi, Suppose I have the following vector (data points): > x [1] 36.0 57.3 73.3 92.0 300.4 80.9 19.8 31.4 85.8 44.9 24.6 48.0 [13] 28.0 38.3 85.2 103.6 154.4 128.5 38.3 72.4 122.7 123.1 41.8 21.7 [25] 143.6 120.2 46.6 29.2 44.8 25.0 57.3 96.4 29.4 62.9 66.4 30.0 [37] 24.1 14.8 56.6 102.4 117.5 90.4 37.2 79.6 27.8 17.1 26.6 16.3 [49] 41.4 48.9 24.1

Hi r-users,   I have a data below but I would like to rearrange my data so that it will be in the following format: year, month, day, rain.  I also would like the data to be arranged so that it will be continues for example year 1939 it will go from january 1 to december 31 and continue with year 1940 from january 1st to 31st December and so on.  What I have now is all january for all the years

Colleagues, I am fitting an Emax model using nls. The code is: START <- list(EMAX=INITEMAX, EFFECT=INITEFFECT, C50=INITC50) CONTROL <- list(maxiter=1000, warnOnly=T) #FORMULA <- as.formula(YVAR ~ EMAX - EFFECT * XVAR^GAMMA / (XVAR^GAMMA + C50^GAMMA)) ## alternate version of formula FORMULA <- as.formula(YVAR ~ EMAX - EFFECT / (1 + (C50/XVAR)^GAMMA)) FIT <-

Dear Community, I have been using two types of survival programs to analyse a data set. The first one is an R function called aftreg. The second one an STATA function called streg. Both of them include the same analyisis with a weibull distribution. Yet, results are very different. Shouldn't the results be the same? Kind regards, J -- View this message in context:

Hi all, just after sending a message to sunmanagers I realized that my question should rather have gone here. So sunmanagers please excus ethe double post: I have inherited a X4140 (8 SAS slots) and have just setup the system with Solaris 10 09. I first setup the system on a mirrored pool over the first two disks pool: rpool state: ONLINE scrub: none requested config: NAME

Hi: I need some help. I am ploting a bar graph but I can't adjust my x axis scale I use this code: i <- qplot(ForkLength,Number,data=FL,geom="bar") i + geom_bar(colour="blue",fill="grey65") # too crowded FL_dat <- ggplot(FL,aes(x=ForkLength,y=Number)) + geom_bar(colour="green",fill="grey65") FL_dat +

Hi Team Can someone advice me on how i can lower the load average on my asterisk server? dahdi-linux-2.1.0.4 dahdi-tools-2.1.0.2 libpri-1.4.10.1 asterisk-1.4.25.1 2 X TE412P Digium cards on ISDN PRI Im using the system as an IVR without any transcoding or bridging ************************************** top - 10:27:57 up 199 days, 5:18, 2 users, load average: 67.75, 62.55, 55.75 Tasks: 149

so I've had a drbd replica running for a while of a 16TB raid thats used as a backuppc repository. when I have rebooted the backuppc server, the replica doesn't seem to auto-restart til I do it manually, and the backupc /data file system on this 16TB LUN doesn't seem to automount, either. I've rebooted this thing a few times in the 18 months or so its been running... not