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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

Hi I'm fairly new to R and am trying to analyse some large spectral datasets using stepwise regression (fairly standard in this area). I have a field sampled dataset, of which a proportion has been held back for validation. I gather than step() needs to be fed a regression model and lm() can produce a multiple regression. I had thought something like: spectra.lm <-

Dear collegues, I´ ve worked with near infrared (NIR) spectroscopy to assess chemical, physical, mechanical and anatomical properties of wood. I use "The Unscrambler" software to correlate the matrix of dependent variables (Y) with the matrix of spectral data (X) and I would like to migrate to R. The matrix of spectral variables is very large (2345 columns and n lines, where n =

Dear colleagues, What did I not understand ? ->my intention I want to create a new variable: In plain language: If someone is taking anithypertensive treatment (med.hyper==1) table(med.hyper) med.hyper 0 1 472 97 I want to subtract 5 mmHg (rr.dia.2m-5) from the measured diastolic blood pressure (rr.dia.2m) if not treated - the value of the measured diastolic blood pressure should

Dear All, using the example from the help of summary.rms library(rms) n <- 1000 # define sample size set.seed(17) # so can reproduce the results age <- rnorm(n, 50, 10) blood.pressure <- rnorm(n, 120, 15) cholesterol <- rnorm(n, 200, 25) sex <- factor(sample(c('female','male'), n,TRUE)) label(age) <- 'Age'

Hello, I am trying to graph a regression line using the followings: Age <- c(39, 47, 45, 47, 65, 46, 67, 42, 67, 56, 64, 56, 59, 34, 42, 48, 45, 17, 20, 19, 36, 50, 39, 21, 44, 53, 63, 29, 25, 69) BloodPressure <- c(144, 220, 138, 145, 162, 142, 170, 124, 158, 154, 162, 150, 140, 110, 128, 130, 135, 114, 116, 124, 136, 142, 120, 120, 160, 158, 144, 130, 125, 175) SimpleLinearReg1=lm(Age ~

Dear list, I've recently become interested in comparing the spectral estimates using the different methods ("pgram" and "ar") in the spectrum() function in the stats package. With many thanks to the authors of these complicated functions, I would like to point out what looks to me like a bit of an inconsistency -- but I would not be surprised if there is good reasoning

Hi, just making some experiments with design library i get an error if i want plot(fit) - show below from onlineHelp !? ..perhaps is here another mask problem?, but label from xtable which was my first problem is now off ! Thanks for advance & regards, Christian $ n <- 1000 # define sample size $ set.seed(17) # so can reproduce the results $ age <- rnorm(n, 50, 10)

Hi, Anne, assign Age and Bloodpressure in the correct order to the axes in your call to plot as in: plot(y = Age, x = BloodPressure) abline(SimpleLinearReg1) Hth -- Gerrit --------------------------------------------------------------------- Dr. Gerrit Eichner Mathematical Institute, Room 212 gerrit.eichner at math.uni-giessen.de Justus-Liebig-University Giessen Tel:

Dear R-helpers, I'm having a problem in using plot.design in Design Library. Tho following example code produce the error: > n <- 1000 # define sample size > set.seed(17) # so can reproduce the results > age <- rnorm(n, 50, 10) > blood.pressure <- rnorm(n, 120, 15) > cholesterol <- rnorm(n, 200, 25) > sex <-

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 $

Hi, When running z <- plot(fit, age=NA, cholesterol=NA, perim=boundaries, method='image') Legend(z, fun=plogis, at=qlogis(c(.01,.05,.1,.2,.3,.4,.5)), zlab='Probability') And after pointing the cursor to the plot() screen in R, I obtain the following message: Using function "locator(2)" to place opposite corners of image.legend Error in

I was messing around with some data in R and SAS (the reason is unimportant) fitting a multiple linear regression and got a curious discrepancy. The data set is too big to post, but if someone wants it, I can send it. So, here are the (partial) results: From R: Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 61.11434 1.48065 41.275 < 2e-16 *** sexWomen

I have a plot produced by function bplot (package = rms) that is really a lattice plot (class="trellis"). It is similar to this plot produced by a very minor modification of the first example on the bplot help page: requiere(rms) n <- 1000 # define sample size set.seed(17) # so can reproduce the results age <- rnorm(n, 50, 10) blood.pressure <- rnorm(n, 120,

From: Cong Wang <amwang at redhat.com> V4: remove some useless #include some coding style fix V3: drop debugging printk's update selinux perm table as well V2: drop patch 1/2, export ifindex directly Redesign netlink attributes Improve netlink seq check Handle IPv6 addr as well This patch exports bridge multicast database via netlink message type RTM_GETMDB.

Hello all, Before getting to my question, I would like to apologize for asking this question here. My question is not directly an R question, however, I still find the topic relevant to R community of users - especially due to only * partial* (current) support for interactive data visualization (see here: http://cran.r-project.org/web/views/Graphics.html were with iplots we are waiting for

Hello, I've a Samba 3.0.23c-SerNet-Debian PDC (no BDC or anything) connected to OpenLDAP. I thought it would work smoothly, I didn't discover any problems until today. I'am trying to create a ntconfig.pol with poledit, but it doesn't show me any groups to add to the policy. I can see all the users by the way. To eleminate a poledit problem I used the security tab (in german

Hi Anne, I would suggest to change the linear model to lm(BloodPressure~Age), as this model makes more sense in biological means (you would assume that age influences pressure, not vice versa) and also obeys the statistical assumption of weak exogeneity, that age can be measured without error, at least compared to error-prone bp measures. Cheers Am 18.04.2018 um 16:07 schrieb Gerrit Eichner:

On Aug 7, 2009, at 21:48, Didier Dambrin wrote: > FLAC doesn't preserve every chunk? I thought it did. I only gave a > quick try > but it seemed to have preserved even the most obscure chunks. > Let me check: it even seems to preserve "MIDI note associated to > marker", > which is a very unknown metadata used by SoundForge (& even defined > in a >

Dear R users: I have a continuous outcome variable and four predictors, two continuous and two dichotomous. i would like to use the lattice plot to create scatter plots for the continuous predictors and boxplots for the dichotomous predictors. with 4 continuous variables, this is what i have been doing: trial = rbind ( cbind ( cimt$ant.mean, cimt$age, 1 ), cbind ( cimt$ant.mean, cimt$sbp, 2 ),