similar to: Interpolate xts

Hello, I am new to R and need some help. I have data in following format DATA matrix ======================== DateTime o h l c 2009-01-01 07:30:00 2 3 4 5 2009-01-01 07:33:00 4 2 5 7 I am able to fill the gap using combination of seq and chron 2009-01-01 07:30:00 2009-01-01 07:31:00 2009-01-01 07:32:00 2009-01-01 07:33:00 x <-

I?m using the new 1.1 integration test facility? I?m trying to write a test that sees if a controller redirects to the correct place and preserves the query string. Here?s the code: class LoginRedirectTest < ActionController::IntegrationTest def test_non_admin_auth request_uri = "/datafeed/event/report?blah=blah" get(request_uri) follow_redirect!

How can achieve this in R using seq, or rep function c(-1,0,1,0,-1,0,1,0,-1,0) The range value is between-1 and 1, and I want it such that there could be n number of points between -1 and 1 Anyone? Please help Thanks Rusty [[alternative HTML version deleted]]

Hello I have trouble getting my original datetime back see below. I hope I am missing something. Please help. > tt <- as.POSIXct("2011-01-07 07:49:13", tz="EST") > tt [1] "2011-01-07 07:49:13 EST" > ttn <- as.numeric(tt) > ttn [1] 1294404553 > tt <- as.POSIXct(ttn,origin='1970-01-01',tz="EST") > tt [1] "2011-01-07

I have been running a program with Wine for over a year. With its version 3 there has been basically no problem. Lately, the program is upgraded to version 4 and it crashes with Wine. I tried to print out debug messages but can't seem to get any clue about what is wrong. While I was testing with the debug messages, an interesting thing I found is that if I run it with the following debug

hello, I have this simple question. This is my dataset size 1 57 2 97 3 105 4 123 5 136 6 153 7 173 8 180 9 193 10 202 11 213 12 219 13 224 14 224 15 248 16 367 17 496 18 568 19 618 20 670 21 719 22 774 23 810 24 814 25 823 I plot it with: plot(generalstats[,1], type="b", xlab="Mesi", ylab="Numero di vertici", main=""); and try to interpolate with a

Dear R Users, I have some data that is very similar in form to a 3D image - ie univariate data on a regular 3D grid. I keep this as a 3D numeric array in R with attributes describing the sampling points along the 3 dimensions. I would like to interpolate this onto a new regular 3D grid that I specify (eg by supplying 3 vectors corresponding to the new grid locations on each of the 3

Hi R-users, I'd like to smooth a matrix to dismiss spikes and to interpolate in plane example of a matrix: Map[1:3,1:3] [,1] [,2] [,3]... [1,] 34.4 34.2 35.1 [2,] 33.4 34.2 35.4 [3,] 34.1 33.2 32.1 .... dim(Map)[1] =/= dim(Map)[2] What functions can I use? Thanks a lot for any response, M [[alternative HTML version deleted]]

Is it possible to interpolate a value for x with knowledge of y? For example, approx(x, y, xout) will give me y's given a set of x's, which is opposite to what I'm after. I've tried switching x and y, e.g., approx(y, x, xout), but in a real data set it is possible to have more than one y for a given x causing approx() to remove coordinates. Thanks for your help, Greg.

I have an very long, irregularly spaced time series (and I'm also new to spectral analysis, so please be patient.) I want to use spec.ls as an interpolator and then use the output to reconstruct the time series via inverse fft. But so far I've been having difficulty doing this. ts<-read.csv("timeseries.csv",header=TRUE) #file contains over 30000 irregularly spaced

Hello, I am an archaeologist who wonders wether a multidimensional (3D) spatial interpolation is possible in R. The data consists of measurements in 3D space with coordinates X-Y-Z and a measured variable U, that is, U is measured at points located at X-Y-Z. e.g. a data structure like the following: X Y Z U 5.10 5.02 16.03 6.674 5.41 4.32 14.03 6.668 1.72 3.59 12.28

Hi all, I have a vector, most of which is missing. The data is always increasing, but may do so in jumps. I would like to interpolate the NAs with 'best guesses', using something like filter(), which doesn't work due to the NAs. Here is an example: > x <- c(2,3,NA,NA,NA,3.2,3.5,NA,NA,6,NA) > x [1] 2.0 3.0 NA NA NA 3.2 3.5 NA NA 6.0 NA I would like a function that

Hi, Please can you tell me what I am doing wrong. When trying to merge two xts objects, one of which has multiple character vectors for columns...I am just getting NAs. > str(t) POSIXct[1:1], format: "2011-01-04 11:45:37" > y2 = xts(matrix(c(letters[1:10]),5), order.by=as.POSIXct(c(t + 1:5))) > names(y2) = c(1,2) > y2 1 2 2011-01-04 11:45:38

I'm having trouble making contour lines for this attached, sparse dataset (low data:NA ratio!). Is it the high number of NA's, or funny layout of the densities, or something else that's causing this? This is a subsample of the dataset, and I get the same problem when using the full data. The only reason I get any contours is because I'm forcing specific levels. If no levels are

Hi all, Issue: I have two datasets, one is a regular time series (rain gauge) with resolution of 10 minutes. The other one is an irregular time series (link). Now I want to analyze the correlation between these two datasets with linear regression. The regular time series is a data.frame and the irregular time series is a zoo object. Problem: For the irregular time series (link) I want also a 10

Dear R-help community, I have looked on the R search site and archives but cannot find mention of a way of interpolating a gaussian distribution of data to a standard 2.5 degree grid. I have two global dataset and I need to correlate - unfortunately one is a 2.5 degree grid dim[longitude=144,latitude=72] and one is gaussian dim[longitude=192,latitude=94]. I would rally appreciate hearing

Hi, I have a very large XTS object. It is about 600,000 entries over 1 year time. I would like to subset a specific piece, by "number of days" not a specific date. The way I do it now is awkward. Would love to find a way to do this easier to generate a new object just containing the days I want. --------------------------------------- dayEnds <- endpoints(dataset,

hi folks, if i have an xts object as follows: library(xts) > dd <- as.POSIXct(strptime(c("2009-06-01 08:00:00", "2009-06-01 08:30:00","2009-06-01 09:00:00","2009-06-02 08:00:00", "2009-06-03 08:00:00", "2009-06-03 08:30:00"),"%Y-%m-%d %H:%M:%S")) > a <- xts(1:6,dd) > a [[alternative HTML version

Is there a easy way to create the time index for a zoo/xts object for every 100 milliseconds. eg. time Index would be: 10:00:00:100 10:00:00:200 10:00:00:300 10:00:00:400 I am looking to build an empty zoo/xts object with time index from 10am to 3pm, index jumps by 100ms each row. Thanks, Chris -- View this message in context:

Hi everyone: I did a search over the internet and still couldn't find answer to my problem. I have a series of prices that I'm trying to clean up by removing any prices greater than 3 times the standard deviations. So, say that prices are: price1 2010-06-18 08:00:06.916 2730 2010-06-18 08:00:07.005 2730 2010-06-18 08:00:07.005 2729 2010-06-18 08:00:07.451