similar to: Weird Excel Time Format

> dput(sensor.sample) structure(c(1328565718.65, 1328566608.9, 1328566162.65, 1328566571.1, 1328566598.85, 1328565634.3, 1328566513.95, 1328565123.65, 1328565827.1, 1328566719.9, 1328565527.55, 1328565118.05, 1328565556.85, 1328565623.85, 1328565230.75, 1328566083.85, 1328566012.45, 1328566795.75, 1328565262.85, 1328566191.35, 1328565827.8, 1328566384.25, 1328565376.95, 1328566006.8,

A sample of the data I have is: > head(sensor) logged_on accx accy accz compassx compassy compassz gyrox gyroy gyroz 1 1326561428000 -0.4602 0.8346 0.0936 0.145508 -0.350586 0.259766 59.617390 28.521740 59.617390 2 1326561428050 -0.4212 1.0452 0.1326 0.219727 -0.321289 0.241211 88.695656 27.478260 88.695656 3 1326561428100 -0.2496 1.3416 0.2886 0.214844 -0.326172

I have a bunch of clean timeseries data obtained from a sensor and I'd like to apply a Kalman Filter to it to smoothe it out. Through a few days of Googling, reading papers, implementing such a filter in various languages, I finally realised that it may be built into R. So I did a "??kalman" at the R prompt and found that it is indeed there. However, the help page is a tad bare,

I have approximately 2.5 million rows from a number of sensor readings. Having plotted these, I can see a given pattern (say a spike in the amplitude away from the mean). I would now like to automate this procedure as we're expecting a great deal more data in the near future. Is there any package or function that will make this possible? Many thanks! I suppose, I could do something like:

I don't know if timeboxing is the correct term to use to accomplish what I'm attempting, so allow me to explain. I have a set n of tagged observations in time series t. What I'm interested in is taking i seconds before and after every n. My code is below: # observations.xts is an xts time series and arg is the number of seconds to for the timebox timeboxes <-

My data: > dput(mydata) structure(list(V1 = c(1328565067, 1328565067.05, 1328565067.1, 1328565067.15, 1328565067.2, 1328565067.25), V2 = c(0.0963890795246276, 0.227296347215609, 0.240972698811569, 0.221208948983498, 0.230898231782485, 0.203282153087549), V3 = c(0.0245045248243853, 0.0835679411703579, 0.0612613120609633, 0.058568910563872, 0.0511868450318788, 0.0557714205674231 )), .Names =

I'd like to get the sum of every other row in a data.frame. When I actually set about doing this, I get the error in the subject line of this message. A sample of my data is below, followed by the function call that should give me the results I want: > dput(head(sens2)) structure(list(Time = c(1328565067, 1328565067.05, 1328565067.1, 1328565067.15, 1328565067.2, 1328565067.25), Y =

I have a list of numbers corresponding to timestamps, a sample of which follows: c(1327211358, 1327221999, 1327527296, 1327555433, 1327701042, 1327761389, 1327780993, 1327815670, 1327822964, 1327897497, 1327897527, 1327937072, 1327938300, 1327957589, 1328044466, 1328127921, 1328157588, 1328213951, 1328236836, 1328300276, 1328335936, 1328429102) I would like to group these into hours. In other

I have two xts objects, call them "a" and "b", and am trying to merge them... > class(a) [1] "xts" "zoo" > class(b) [1] "xts" "zoo" > head(a) 2010-04-01 7.6343 2010-04-02 7.6343 2010-04-03 7.5458 2010-04-04 7.4532 2010-04-05 7.4040 2010-04-06 7.3317 > head(b) 2010-04-01 568.80 2010-04-05 571.01 2010-04-06

Dear all, I have a time serie dataset such as the following with data acquired every 15 minutes: Date Heure Profondeur Temp?rature Salinit? Turbidit? Chloration 1 2012-07-06 08:47:22 -0.144 22.469 0.011 0.000 0 2 2012-07-06 09:02:21 -0.147 22.476 0.011 0.000 0 3 2012-07-06 09:17:21 -0.139 22.498 0.011 19.323 0 4 2012-07-06

Can't installe packag maDB or limma. Error is shown as Using R version 2.13.1, biocinstall version 2.8.4. Installing Bioconductor version 2.8 packages: Is there any other way to draw volcano plot ? Thanks [[alternative HTML version deleted]]

When I run the code below on Macintosh and Windows, the plot comes out fine. However, on Linux, the png generated is invalid from R console, and loading strucchange crashes rkward. Is this a known issue on Linux and, if so, is there a workaround? Many thanks! require(strucchange) data("RealInt") bp.ri <- breakpoints(RealInt~1, h=15) summary(bp.ri) fac.ri <- breakfactor(bp.ri,

I'm trying to read in a CSV, with lines looking like: HEADER, Latitude DecDeg, Latitude Hemisphere, Longitude DecDeg, Longitude Hemisphere, Speed knots, Bearing Degrees, fixQualityGga, noOfSatGga, altGga, heightGga, selectionGsa, fixGsa, pdopGsa, hdopGsa, vdopGsa, noOfSatGsv, Time, *checkSum $GPS, 3747.0224, N, 12223.4522, W, 0.36, 348.21, 1, 3, 4.01, 175.5, -25.2, A, 2, 4.14,

I have a list of bounds for a series of polygons. I do understand the formula to determine whether point i is within polygon X (X[x1] < i[x] & X[x2] > i[x] & X[y1] < i[y] & X[y2] > i[y]), and I can apply this throughout the dataset. However, this naive algorithm doesn't scale very well. The data set contains 10,000 points consisting of (n,e) pairs where I'm

Not sure if the question is appropos, but I have multiple csv's which are read into an xts object, corresponding to telemetry data (accelerometer, magnetometer/compass, and gyroscope). For examination, it would be ?ber useful if plot.zoo (or something similar) allowed me to zoom in and out of a subset of the time axes. -- Sent from my mobile device Envoyait de mon portable

Thanks to Joshua Wiley for turning me on to ggplot2. I am making a plot using this: p <- ggplot(dallas, aes(x = offense_hour)) + geom_bar() + coord_polar() Dallas is a data frame, and offense_hour is a column with chron objects from the chron library. In this case, the chron object was created with the times function. It is only a time (H:M:S) with no date attached. The plot shows up fine,

Hello, Is there a web version of this R-Help user group (such as the ones under Google Groups) such that 1. I can do a search on any topic over thousands of posts on R easily and effectively 2. My mailbox do not overflow with emails so that I do not need to edit it every day 3. I can arrange to receive only the responses to my posts automatically 4.

Hi! I''m looking for a good tutorial that explains the main points of performing queries with Rails. I do have AWDWR and have read the section on ''find'' but I''m looking for something that goes into more detail on how to perform queries across tables. Abstracted from my current application, this is an example: * person has_many sites * site has_one room *

I would like to get at all models in a rails application to be able to add a field to every one of them as part of a migration. Something like the following: Appmodels.each { |x| add_column x.table_name.to_s, :foo, :text } I understand I can get the table name using ActiveRecord::Base#table_name, but how do I get all the models into an array that I can use in the above manner? -- Cheers, Hasan

I just installed ruby, lighttpd, and mysql from darwinports on me laptop in lieu of the Apple version of ruby. Now when I fire up my rails application, it''s not running lighttpd anymore -- it''s running webrick. It also exits immediately. MySQL is running, the database and tables are restored from the backup. What step am I missing? Thanks for the help! Cheers, Hasan