similar to: tsdiag and tsStructure for np,ns,nt and nl determination

Dear all, Is there a simple trick to read in data with the following format and create a Time Serie object of it? Date CountOfField2 5/10/1998 7 5/11/1998 5 5/12/1998 2 5/14/1998 1 5/15/1998 1 5/19/1998 1 5/20/1998 1 5/21/1998 1 5/24/1998 2 5/25/1998 1 5/26/1998 2 .... 2002 ... R should recognize that some dates are not available...(NA). You can define start and end date Ok, and frequency= 365

Dear, Thanks for the previous tips about 'its' for importing the following data. 5/10/1998,7 5/11/1998,5 5/12/1998,2 5/14/1998,1 5/15/1998,1 5/19/1998,1 5/20/1998,1 1. When using the following command; test<-readcsvIts('Fires98.csv',informat=its.format("%m/%d/%Y"),header=FA LSE) the function reads in the data from the csv file as; V2 05/10/1998 7

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!

Dear, I'm looking for some examples on OO programming in R. I have the programming manual with explanation on UseMethod and NextMethod but I miss some practical examples to get me going (I hope). I searched the web but could not find a good independent tutorial on this. Any suggestions are welcome, Kris -- ------------------------------------------------------------------------

Dear, I have XYZ data available in a MySQL database. I get it out, can plot the data with the plot() function, load it into a geoR datastructure. But what I actually would like to do is a simple contouring of the data based on a no Kriging interpolation such as TIN based. I know the first thing I shold do is interpolate a full matrix for the region I have my points for, then contour should

Dear, we have a problem with geoR. We try to read an ASCII table (x,y,z) with 40000 lines. With read.geodata we get the error: Error in vector("double", length) : cannot allocate vector of length 799980000 We can read the file without any problem with read.table, but trying to convert it to the geodata class gets the same error. Any help/tips would be appreciated. Kris, Dave --

Hi, I can't figure out how to get the P-values out of the summery of a logistic regression. I used: logit.out <- glm(...) and then I should be able to extract just the P values for the coefficients. Any idea? Kris -- ------------------------------------------------------------------------ http://perswww.kuleuven.ac.be/~u0027178/VCard/mycard.php?name=krisn

Hi, I looked for the nls() function and couldn't find it. In the refman.pdf it's mentioned as part of the nls package which I cannot find and I also read something about the MASS package, also impossible to find for me. Kris -- ------------------------------------------------------------------------ http://perswww.kuleuven.ac.be/~u0027178/VCard/mycard.php?name=krisn

Dear, We are trying to read an asciifile using the read.table() function and discovered that only 4 decimals are read. Any idea how to get more decimals? Kris -- ------------------------------------------------------------------------ http://perswww.kuleuven.ac.be/~u0027178/VCard/mycard.php?name=krisn ------------------------------------------------------------------------ Minds are

Hi, I'm new to R and looking for a way to use a variable to reference to an object. I'm plotting several graphs on top of each other and want to do this by a for loop. The field I want to graph have names like a1,a2,a3, ... I can't figure out how to get this working: It should look like this: lines(spectral$Wavelength,paste("spectral$a",j,sep=""),col=j) but

Hello, I'm getting the following error message when I try to run 'tsdiag' on what seems to be a valid time series: > tsdiag(small) returns: [Error in tsdiag(small) : no applicable method for "tsdiag"] where small is a little test series where I have isolated this problem (the original has 30-years worth of daily data) When I print it (small), it looks like the

I am using the ts package to fit ARIMA models, and the tsdiag() function to plot diagnostics. In doing so I'm generating an awful lot of diagnostic plots of different models and different data sets all within the same R session. So my question is, is there an option in tsdiag() similar to <main="Title"> that I can use? This would be quite helpful when I print out the plots,

Dear Everyone, The document of `tsdiag? says > These tests are sometimes applied to the residuals from an ARMA(p, q) fit, in which case the references suggest a better approximation to the null-hypothesis distribution is obtained by setting fitdf = p+q, provided of course that lag > fitdf. This implies that we should pass the `fitdf' parameter when applying `Box.test' to

HI list, I want to know whether tsdiag uses k-(p+q) as the lag in ljung box test. How is it possible to save those values nuncio -- Nuncio.M Research Scientist National Center for Antarctic and Ocean research Head land Sada Vasco da Gamma Goa-403804 [[alternative HTML version deleted]]

Hi all, I am modelling a time series with missing data. *Q1)* However, I am not sure if I should use the next *graphics* to understand my data: *a)* ACF & PACF (original series) *b)* ACF & PACF (residuals) * * *Q2)* I am using *tsdiag*, so I obtain a graphic with 3 plots: stand. residuals vs time; acf for residuals; Ljung-Box for residuals (it is wrong for residuals). I know that using

I am drawing two plots on the same graphics device window as follows: yLim<-range(range(template),range(slope*subSeries) ) plot( template, type="p", pch=19,cex=1.75,lwd=2.5,lty=1, ann=F, axes=F,frame.plot=T,col="red", ylim=yLim,new=T ) title( main = "myDotChart of original template and subSeries vs time" );points( slope*subSeries, type="p",

The "tsdiag" function in the TSA package overrides the "tsdiag" function in the "stats" package. There are a few annoying bugs in the TSA's version of the function so I would like to use the "stats" function but still have access to other TSA functions. I have tried using stats::tsdiag( ) but as long as the TSA package is attached the function from

Dear list, R-core, The documentation of stats::stl explicitly refers to the paper by Cleveland[1] to explain the parameters. However, the description is confusing, with two descriptions seeming to refer to the same parameter in the paper. s.window: [...] the loess window for seasonal extraction, which should be odd and at least 7, according to Cleveland et al --> The phrase 'odd and at

Just by re-examining my question I found the answer ! segments(3, template[3], 3,slope*subSeries[3], col= "orange",lwd=2)I corrected the subSeries Points as they appear on the graph withslope*subSeries[3].thank youLloyd L [[alternative HTML version deleted]]

Hi, I saw that tsdiag function doesn't provide a correct result for Ljung-Box test. I want to use Box.test function for this, but I don't know how to determine lag parameter for this function. For fitdf, as I'm using a SARIMA model (0,1,1)(0,1,1)12, I decided to set it to 2. Can you confirm me the value for fitdf and give me a way to determine the lag value? Thanks Myriam -- View