similar to: x-axis in plots and interaction.plots

Time Series functions in R ========================== I think a good basic S-like functionality for library(ts) in base R would include ts class, tsp, is.ts, as.ts plot methods start end window frequency cycle deltat lag diff aggregate filter spectrum, spec.pgram, spec.taper, cumulative periodogram, spec.ar? ar -- at least univariate by Yule-Walker arima -- sim, filter, mle, diag, forecast

Hi All, I have two time series, each has length 354. I tried to calculate the coherency^2 between them, but the value I got is always 1. On a website, it says: " Note that if the ensemble averaging were to be omitted, the coherency (squared) would be 1, independent of the data". Does any of you know how to specify properly in R in order to get more useful coherency? The examples in

hello, I have been using the per function in package longmemo to obtain a simple raw periodogram. I am considering to switch to the function spec.pgram since I want to be able to do tapering. To compare both I used spec.pgram with the options as suggested in the documentation of per {longmemo} to make them correspond. Now I have found on a variety of examples that there is a shift between

Thanks for your reply Nassar. What I really want is to overlay (like add=TRUE) the plots 1 and 2. With plots "at the same screen" I meant overlaid and not one beside the other, i.e., only one plot with all the points (1 to 10) in blue (or any other color), the points 5 to 9 in red and a regression line from points 5 to 9. Best regards, Antonio Olinto ----- Original Message -----

Hello everyone, This is my first time posting to the list, thanks in advance. I am calculating the smoothed periodogram for the residuals of an AR model that I fit to EEG data. The autocorrelation plot of the residuals shows the series is now approximately white (i.e. ACF = 1 at lag 0, and close to 0 for all other lags). I would like to show that the spectrum of the series is also

Hi, I'd like to find which values of x will give me a y. In other words, in the example of a gaussian curve, I want to find the values of x that will give me a density, let's say, of 0.02. curve(((1/(sqrt(2*pi)*10))*exp(-((x-50)^2)/(2*10^2))),xlim=c(0,100)) Thanks for any help, Antonio Olinto ------------------------------------------------- WebMail Bignet - O seu provedor do

Greetings, I would like to estimate a spectral coherence between two timeseries. The stats : spectrum() returns a coh matrix which estimates coherence (squared). A basic test which from which i expect near-zero coherence: x = rnorm(500) y = rnorm(500) xts = ts(x, frequency = 10) yts = ts(y, frequency = 10) gxy = spectrum( cbind( xts, yts ) ) plot( gxy $ freq, gxy $

Hello world, I am actually trying to transfer a lecture from Statistica to R and I ran into problems with spectral analysis, I think I just don't get it 8-( (The posting from "FFT, frequs, magnitudes, phases" from 2005 did not enlighten me) As a starter for the students I have a 10year data set of air temperature with daily values and I try to get a periodogram where the annual

I have done a fair bit of spectral analysis, and hadn't finished collecting my thoughts for a reply, so hadn't replied yet. What exactly do you mean by normalize? I have not used the functons periodogram or spectrum, however from the description for periodogram it appears that it returns the spectral density, which is already normalized by frequency, so you don't have to worry about

Dear R users I have a really simple question (hoping for a really simple answer :-): Having estimated the spectral density of a time series "x" (heart rate data) with: x.pgram <- spectrum(x,method="pgram") I would like to compute the power in a specific energy band. Assuming that frequency(x)=4 (Hz), and that I am interested in the band between f1 and f2, is the

Dear R-list members, Some months ago I wrote a message on the usage of gnls (nlme library) and here I come again. Let me give an example: I have a 10 year length-at-age data set of 10 fishes (see growth.dat at the end of this message) and I want to fit a von Bertalanffy growth model, Li= Linf*(1-exp(-k*(ti-t0))) where Li = length at age i, Linf= asymptotic length, k= curvature parameter, ti=

Dear R-List members, I want to check if a set of measurements follows better a gamma or a lognormal distribution (see data below). Using shapiro.test I can test for normality (shapiro.test(log (Lt)). To test for gamma (and normal) distribution I would use ks.test but I need to specify its shape and scale. How should I calculate these values in R? I tried > Lt.fit <- glm(Lt ~ 1,

Dear R-list members Here goes a question on data frames: I want to create a new data frame excluding some records (rows) from an existing one. Considering the data frame "fish.dat" at the end of this message, I can make a boxplot(Ring~Radius) and identify the points at rows 11 and 25 as outliers. With the command fish.dat[c(11, 25),] I can identify which fishes are related to

Dear R experts, beginners and everyone else, I'm calculating "cumulative periodogram" using the command "cpgram" [1] from the MASS library. Here is a short example with the "lh" (hormone level) dataset: library(MASS) plot(lh,type="l",ylab="value",xlab="time", main="Hormone Levels (lh)") spectrum(lh,

Antonio, For linear regression we have the following identity total SS = regression SS + residual SS (*) where total SS is the sum of squares of observations around their mean, i.e. total SS = (n-1)*var(y) and residual SS is given by the deviance function. R-squared is defined as R^2 = regression SS/ total SS = 1 - residual SS/total SS. You can use this last formula

?summary.lm says, under the "Value" section, coefficients: a p x 4 matrix with columns for the estimated coefficient, its standard error, t-statistic and corresponding (two- sided) p-value. so try summary(fit.lm)$coefficients[,1:2] to get the coefficients and their SEs. For nls, it takes a bit more digging, as the documentation is a bit sparse. Something

Hi, Some time ago I asked about how to use comma as decimal separator in plots and Mr. Paul Murrell wrote: ------- You could try something with axis() and chartr(), like ... par(mfrow=c(2,1)) plot(1:10/11, rep(1, 10), main="Standard X-Axis") plot(1:10/11, rep(1, 10), main="Customised X-Axis", axes=F) axis(1, at=pretty(1:10/11),

Hi, I want to write in x axis label "fitted value of lambda" (lambda in greek letter). xlab=expression(lambda) gives the "lambda", I tryed things like xlab=paste ("fitted value of ", expression(lambda)) but I didn't get the greek letter. Thanks in advance for any hint. Antonio Olinto ------------------------------------------------- WebMail Bignet - O seu

Hi everyone Can anyone tell me how I normalise a power spectral density (PSD) plot of a periodical time-series. At present I get the graphical output of spectrum VS frequency. What I want to acheive is period VS spectrum? Are these the same things but the x-axis scale needs transformed ? Any help would be greatly appreciated Tom

> Cordial saludos a tod en s. > > Estoy leyendo un tema y tengo la siguiente necesidad. > > Los contacto para pedirles MUY ENCARECIDAMENTE ME AYUDEN con la > explicación DE CÓMO HACER EL MODELO ARMA en R DE UNA SEÑAL CUALQUIERA para > obtener de ella el modelo matemático fraccional aproximado, esto para > obtener el PSD de la señal (Power Density Spectrum). > > La