similar to: KalmanSmooth

I have a 10-column XLS file, with 2 date fields. As far as I can tell, they were configured identically in Excel 2010. One of these fields resembles "39406.577662037", whilst in Excel, it is shown as "2007-11-20 13:42:20". Applying as.Date() with the default format doesn't do it. Any ideas as to what format this is? Many thanks! -- H -- Sent from my mobile device Envoyait

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

Hello, I would like use Kalman filter for estimating parameters of a stochastic model. I have developed the state space model but I don’t know the correct way use Kalman filter for parameter estimation. Has anybody experience in work with Kalman filter in R. I don’t know the correct function. Maybe it is - KalmanLike; but what is the correct Input? - tsmooth? -

Hi My name is Vladimir Samaj. I am a student of Univerzity of Zilina. I am trying to implement Kalman Filter into my school work. I have some problems with understanding of R version of Kalman Filter in package stats( functions KalmanLike, KalmanRun, KalmanSmooth,KalmanForecast). 1) Can you tell me how are you seting the initial values of state vector in Kalman Filter? Are you using some method?

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 =

> 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,

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 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:

Hello, In R I am trying to use Kalman filtering to find a solution for an hydrological problem. With Kalman Filtering I want to estimate the discharge comming from three storage bassins. I have programmed a function in R which can run KalmanSmooth. When I'm asking for the function and putting in values, R detects the following error: "Error in as.vector(data) : Argument "S1" is

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

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 R Helpers, Currently I'm working with the ts package of R and created a TimeSerie from pixels extracted from satellite imagery(S10 NDVI data, 10 daily composites). I'm trying to decompose this signal in different signals (seasonal and trend). When testing out the STL method is says => Only univariate timeseries are allowed, but the current Timeserie I'm using is univariate!

Hi, I would like to know what should I garantee about P and GGt in order to have F = Z %*% P %*% t(Z) + GGt always as a positive definite matrix. Being more precise: I am trying to find minimum likelihood parameters by using the function 'optim' to find the lowest value generated by $LogLik from the function 'fkf' (http://127.0.0.1:27262/library/FKF/html/fkf.html). The

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

Hola! I got problems using an objects returned from arima (in KalmanSmooth(my.ts, ModArima$model), because my.ts showed up to have storage mode "integer" (is.integer(my.ts was TRUE). Should storage.mode() of a ts be allowed to be integer, should ts() someplace say storage.mode(ts.out) <- "double", or maybe inside arima() storage.mode(x) <- "double"

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]]

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 *