similar to: Three questions about a model for possibly periodic data with varying amplitude

Hi dear R community, I have up to 12 measures of a protein for each of 6 patients, taken every two or three days. The pattern of the protein looks periodic, but the height of the peaks is highly variable. I'm testing for periodicity using a Monte Carlo simulation envelope approach applied to a cumulative periodogram. Now I want to predict the location of the peaks in time. Of course, the

Dear R-helpers, I have time series data from 16 subjects and 2 treatment groups. The seasonal variation can be best described by two harmonics, I called the frequencies omega and omega2. I now want to test whether (1) the seasonal pattern differs between the treatments (some kind of overall test). If this is the case, (2) I want to conduct tests to find out whether the amplitude of the

Dear list, I apologies first for my English, hope you will understand well my question. I am working on 1/2 hour piezometric data, time unit is second. They present daily oscillation when using the spectrum() function. What I am really interested in, is to find the amplitude corresponding to this oscillation. I work with a college using Matlab, and although we apply the same methodology, our

I did a fourier transform on a function in time domain to get the following functions in frequency domain (in latex): $Y_1[\omega] = \frac{1}{1-\phi_1 e^{-jw}}$ $Y_2[\omega] = \frac{1}{1-(\phi_1 + \phi_2)e^{-jw} +\phi_1\phi_2e^{-2jw}}$ How do I find the spectrum of this function for given $\phi_1$ and $\phi_2$ coefficients and in the discretization interval $w = [-\pi:.1*\pi: \pi]$? Then, how

I have been attempting to estimate the periodic contribution of an effect to some data but have not been able to fit a sine wave within R. It would be nice to start by being able to fit a sine wave with an amplitude and frequency. x<-seq(0,20,by=0.5) y<-2*sin(2*pi*.5*x) #amplitude =2, frequency=0.5 # This failed to converge r<-nls(y ~ A*sin(2*pi*F*x), start=list(A = 1, F = 1),

dfhfsdhf at ghghgr.com I ran a simple lme model: modelrandom=lmer(y~ (1|Test) + (1|strain), data=tempsub) Extracted the BLUPs: blups=ranef(modelrandom)[1] Even wrote myself a nice .csv file....: write.csv(ranef(modelrandom)[1],paste(x,"BLUPs.CSV")) This all works great. I end up with a .csv file with the names of my strains in the first column and the BLUP in the second

Dear list, What on earth is spec.pgram() normalized too? If you would like to skip my proof as to why it's not normed too the mean squared or sum squared amplitude of the discrete function a[], feel free too skip the rest of the message. If it is, but you know why it's not exact in spec.pgram() when it should be, skip the rest of this message. The issue I refer herein refers only too a

Hi all, To follow up on an older thread, it was suggested that the following would produce confidence intervals for the estimated BLUPs from a linear mixed effect model: OrthoFem<-Orthodont[Orthodont$Sex=="Female",] fm1OrthF. <- lmer(distance~age+(age|Subject), data=OrthoFem) fm1.s <- coef(fm1OrthF.)$Subject fm1.s.var <- fm1OrthF. at bVar$Subject fm1.s0.s <-

I have the following dataset: 96 plots 12 varieties 2 time points The experiment is arranged as follows: A single plot has two varieties tested on it. With respect to time points, plots come in 3 kinds: (1) varietyA, timepoint#1 vs. variety B, timepoint#1 (2) varietyA timepoint #2 vs. varietyB timepoint #2 (3) varietyA timepoint #1 vs. variety A timepoint#2 - there are 36 of each kind

Dear R users, I have a question about the patterned variance-covariance structure for the random effects in linear mixed effect model. I am reading section 4.2.2 of "Mixed-Effects Models in S and S-Plus" by Jose Pinheiro and Douglas Bates. There is an example of defining a compound symmetry variance-covariance structure for the random effects in a split-plot experiment on varieties of

Hello, I have two tab-delimited files which I would like to combine. In the first one I have gene IDs (Unique) on column 1 and than various experimental results from microarray analysis (see attached files list1 ) the second arrays have the same genes IDs (more and in a different order, some are double) (see attached files list2 ) What I would like to do is to search in the second list for gene

for the script, please kindly see the script below. At line 10 and line 13, my problems occurs. The first one is I try to retrieve the gene official name from a column of a table. The pattern of official name is something starting with gene_name. For detail problems, please see the according lines. Any suggestions are appreciated example of matching source (extract the Nnat, sometime it would

Dear all, I try to use read.table to get the data from a tab delimited file, and some of the data is shown below: 3185 heterogeneous nuclear ribonucleoprotein F 3187 heterogeneous nuclear ribonucleoprotein H1 (H) 3188 heterogeneous nuclear ribonucleoprotein H2 (H') 3189 heterogeneous nuclear ribonucleoprotein H3 (2H9) 3190 heterogeneous nuclear ribonucleoprotein K ///

When I call inbound with a cell phone (via SIP PSTN trunk) some of my prompts the first word is cut off. I'm assuming the prompt is needing to be transcoded on the fly and it's not getting transcoded fast enough. I did a file convert to create gsm versions (currently they are referenced in my dial plan with no extension Seem to have same problem. How do I determine which file

Using a more stable nonlinear modeling tool will also help, but key is to get the periodicity right. y=c(16.82, 16.72, 16.63, 16.47, 16.84, 16.25, 16.15, 16.83, 17.41, 17.67, 17.62, 17.81, 17.91, 17.85, 17.70, 17.67, 17.45, 17.58, 16.99, 17.10) t=c(7, 37, 58, 79, 96, 110, 114, 127, 146, 156, 161, 169, 176, 182, 190, 197, 209, 218, 232, 240) lidata <- data.frame(y=y, t=t) #I use the

Hello everyone, I would like to parse very large xml files from MS/MS experiments and create R objects from their content. (By very large, I mean going up to 5-10Gb, although I am using a 'small' 40M file to test my code.) My first attempt at parsing the 40M file, using the XML package, took more than 2200 seconds and left me quite disappointed. I managed to cut that down to around 40

What I am trying to do is use GUI function, traitr, and to call for a pdb file and save it and then display it. I want to call for it by taking it from the user and then displaying it on the screen. I am having problems with that. The line pdb <- read.pdb(""ProteinCode) where proteincode should be the name of the protein, for example 1ly2, but it always ends up being protein. My

Dear Colleague, Happy New Year! As we know, codon preference among different species could be dramatically different. To enhance the expression level of a foreign protein in a particular expression system (E.coli, Yeast, Insect, or Mammalian cell), it is very important to adjust the codon frequency of the foreign protein to match that of the host expression system. One classic example is GFP

Dear Colleague, Happy New Year! As we know, codon preference among different species could be dramatically different. To enhance the expression level of a foreign protein in a particular expression system (E.coli, Yeast, Insect, or Mammalian cell), it is very important to adjust the codon frequency of the foreign protein to match that of the host expression system. One classic example is GFP

Hi I am trying to read selected fields from a xml file with R using xml package. So far I have learned the basics of this package by going through the manual, examples, tutorial, and so on (www.omegahat.org/RSXML) . The problem is that I am getting stuck when it comes down to more complex xml files. I am a novice in R and xml, and was wondering if someone could help me out with here.