similar to: Sas by function in R

is there a way to use the actual index value for plotting zoo objects this is the way that the index is set up and a sample range of what I would like to plot 01/01/06 00:00:00 - 01/01/06 23:45:00 { library(zoo) # chron library(chron) fmt.chron <- function(x) { chron(sub(" .*", "", x), gsub(".* (.*)", "\\1:00", x)) }} x <- structure(c(15.57, 15.5,

Hi, I am very new to R and I've been trying to work through the R book to gain a better idea of the code (which is also completely new to me). Initially I imputed my data from a text file and that seemed to work ok, but I'm trying to examine linear relationships between gdist and gair, gdist and gsub, m6dist and m6air, etc. This didn't work and I think it might have something to do

Hello, I have to add "Age (bar(x)=14.3) as a title on a chart. I am unable to get this to working. I have tried bquote, substitute and expression, but they are only doing a part of the job. new<- c(14.3, 18.5, 18.1, 17.7, 18, 15.9, 19.6, 17.3, 17.8, 17.5, 15.4, 16.3, 15, 17.1, 17.1, 16.4, 15.2, 16.7, 16.7, 16.9, 14.5, 16.6, 15.8, 15.2, 16.2, 15.6, 15, 17.1, 16.7, 15.6, 15, 15.8, 16.8,

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

Dear all, I am attempting to explain patterns of arthropod family richness (count data) using a regression model. It seems to be able to do a pretty good job as an explanatory model (i.e. demonstrating relationships between dependent and independent variables), but it has systematic problems as a predictive model: It is biased high at low observed values of family richness and biased low at

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! I tried to perform Shapiro-Wilk test for my sample of 243 values. > Us [1] -10.4 -13.1 -12.2 38.1 -18.8 -13.3 -11.7 29.3 49.7 6.8 12.7 16.3 [13] 5.8 -0.7 -29.4 4.1 38.8 -1.4 8.8 15.6 32.9 -5.3 19.1 35.8 [25] 4.0 -1.5 0.6 -4.2 -10.0 -4.0 1.1 48.9 -21.0 -5.3 5.8 -10.8 [37] 21.9 8.2 -3.2 -3.9 -2.3 12.6 -4.7 -8.0 11.8 27.4 -9.5 -20.8 [49]

How can I tell if this is normal behaviour? Oracle imports are horribly slow, an order of magnitude slower than on the same hardware with a slower disk array and Solaris 9. What I can look for to see where the problem lies? The server is 99% idle right now, with one database running. Each sample is about 5 seconds. I''ve tried setting kernel parameters despite the docs saying that

hi I plot a series of observation data every minutes in a day as the attachment below plot(wnd,type='l',lty=1,col='red',lwd=1,xlab=xxlab,ylab=yylab,ylim=YY) In the figure, the x-axis tickment is the number of data How can I change it fore example 1h 2h 3h 4h and so on ? -- TANG Jie Email: totangjie at gmail.com Tel: 0086-2154896104 Shanghai Typhoon Institute,China

hello, I'd like know how to sort a data frame in R for example how I should do to sort by Catholic with swiss data frame like below thanks Fertility Agriculture Examination Education Catholic Infant.Mortality Courtelary 80.2 17.0 15 12 9.96 22.2 Delemont 83.1 45.1 6 9 84.84 22.2

Hello, I have a binary file type that includes a zlib compressed data block (ie not gzip). Is anyone aware of a way using base R or a CRAN package to decompress this kind of data (from disk or memory). So far I have found Rcompression::decompress on omegahat, but I would prefer to keep dependencies on CRAN (or bioconductor). I am also trying to avoid writing yet another C level interface to

Dear all- I have a dataset (see a sample below - but the whole dataset is June 2005 - June 2008). The "LST" format is "YYMMDDHHmm" and I would like to get the hourly average of the "mph" for the summer months (spanning all years). I have been trying to use "aggregate" but am not having much success at all! any thoughts would be greatly appreciated.

Hi, I haven't tried the code yet. Is there a way to parse this data using R and create bar plots so that each program's 'RAM used' figures are grouped together. So 'uuidd' bars will be together. The data will have about 50 sets. So if there are 100 processes each will have about 50 bars. What is the recommended way to graph these big barplots ? I am looking

Hi there I thought this would be of particular interest to people using 'optim' functions and perhaps people involved with R development. I've been beaten down by R trying to get it to perform an optimization on a mass-balance model. I've written the same program in excel, and using the 'solver' function, it comes up with an answer for my variables (p, ACT, which

Hi, My error isErro em hist.default(dados[[1]], freq = TRUE, seq(0, 30, 0.5), prob = FALSE, : some 'x' not counted; maybe 'breaks' do not span range of 'x' hist(dados[[1]],seq(0, 30, 0.5), prob=TRUE, xlab="chuva (mm/dia)",ylab="frequência", main="", cex.lab=1.6, cex.sub=3,cex.axis=3,cex.main=6) Someone help me? [[alternative

Greetings, I would like to plot three lines on the same figure, and I am lost. There is an answer to a similar thread… but I tried matplot and it is beyond me. An example of the data follows: Year EM IM BM 1983 9.1 16.8 -7.7 1984 12.0 18.0 -6.0 1985 13.6 19.1 -5.5 1986 12.4 17.3 -4.9 1987 14.6 20.3 -5.7 1988 20.6 23.3 -2.6 1989 25.0 27.2 -2.2 1990 28.4 30.2 -1.8 1991 33.3 31.2 2.1 1992 40.6

Dear R-User, Appreciate any helps. It looks simple, but I don't have a clue. Given that I have a dataframe of tree population with three variables: sp=species , d0=initial_size grow=growth increment from initial size per year How can I calculate the future growth increment of each tree for the next 3 years. The following Rscript was written, #---------- a0 <-

Hola!! tengo un data.frame donde cada fila corresponde a un año y cada columna a un mes (De enero a diciembre) > head(valT) V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 1941 18.0 16.3 15.2 10.1 8.1 8.3 8.8 9.2 7.9 12.2 11.9 14.6 1942 17.2 15.9 13.6 11.6 8.7 6.2 6.4 7.2 9.7 12.0 14.1 16.7 1943 17.6 17.3 13.5 12.5 10.5 7.0 8.2 7.9 -999.9 -999.9

Hello R Users, I am new to R. I have two data sets i) TOMS aerosol optical depth(AOD) and ii) TOMS ozone(O3). > > AOD data is on 1x1 grid and O3 data is on 5x5 grid. > > First I want to read AOD and O3 as it is and then I want to regrid AOD on > 5x5 grid as O3. > > Reading is first problem. > > FIRST PROBLEM READING AOD: > > AOD data is in following format: >

Hi everyone, I've run into a bit of strange problem with implicit vs explicit printing and the call stack. I've included an example at the bottom of this email. The basic problem is that I have an S3 object with a print method. When the object is implicitly printed (ie. typed directly into the console) the function arguments in the call stack are exploded out to their actual values,