similar to: repeated measures with gls

Hi I'm using kronecker() with a matrix and a vector. I'm interested in the column names that kronecker() returns: > a <- matrix(1:9,3,3) > rownames(a) <- letters[1:3] > colnames(a) <- LETTERS[1:3] > b <- c(x=1,y=2) > kronecker(a,b,make.dimnames=TRUE) A: B: C: a:x 1 4 7 a:y 2 8 14 b:x 2 5 8 b:y 4 10 16 c:x 3 6 9 c:y 6 12 18 > The

Dear R Community, I am trying to optimize a water quality model that I am using. Based on conversations with others more familiar with what I am doing I plan to implement DEOptim to do this. The water quality model is interfaced through a GUI. I have the input file necessary to alter parameters and run the model as a text file. To do the optimization I have figured out the general procedure

Dear R-users Thanks to Jose Pinheiro, Douglas Bates and coworkes for providing R with the nlme package. Could someone help me, please, to specify a correct random formula for a mixed model, that specifies no random effect on a higher level? I have the following dataset of timeseries of respiration measurements (column resp) of biomass including a parameter initial biomass x0. Respiration

I am trying to plot fitted lme values as a smooth line of a graph showing the exponential relationship between temperature and soil respiration. In the plot, the x-axis has temperature, and the y-axis has soil respiration. When I try to add a line showing temperature versus the fitted values, it is jagged and not smooth. Here is the code I used: lme.1<-lme(fixed=LnFlux~Temp,

How are sub/superscripts designated for text in axis labels? As in this y-axis label: scale_y_continuous("Respiration, pmol O2 h-1") where the "2" needs to be subscripted and the "-1" needs to be superscripted. Thanks. Adam --------------------------------------------------- Adam G. Marsh, Ph.D. Associate Professor Marine Biological Sciences University of

Hi- A journal has asked me to make all of my text annotations on a figure at 10-point size. For the most part this is easy, e.g. by creating figures with: pdf(..., family='Times', pointsize=10) But where I have superscripts (or subscripts) in axis labels, the default seems to be to shrink the superscripted text slightly. For example this code:

Guys. Ive been testing how to receive faxes using TDM400P cards and so far, after playing with gains, echocancell and echotraining on zapata.conf.. Ive ha dno luck, faxes come in as garbage or broken or with blank lines. Anybody has successfully done this? Any tips.. Also I have some ideas: 1. Is it really possible to get fxes on a fax machine using ATAs like the sipura 2002? Even using ulaw

Hello. My name is Ana. I?m doing an eology master, and I?m just learning how R works. I have a Mac OS X 10.5.6, and I?m tryng to run just a simple ANOVA nanalyses. I dowloaded R version 2.10.0, and it seems I have problems with the script. I don?t know what to do, I?ve already change the languages, be sure of being working in the correct directory and doesn?t work the script is: #1. example

We are trying to build a human respiration model. Preliminary analysis of some breathing signals has shown that humans breathe through switching among a finite number of patterns. Hidden Markov seems to be the right approach. Since most of our code is written in R scripting language, finding an R package implementing an HMM that we can use for our prototype would be very helpful. I have been

Hello R users, When trying to fit a nonlinear mixed model to a respiration time series, I get the following error message: Error in recalc.varFunc(object[[i]], conLin) : dims [product 30] do not match the length of object [34] In addition: Warning message: In conLin$Xy * varWeights(object) : longer object length is not a multiple of shorter object length Below is an example that generates

Hello , I'm new to R and don't really understand how to use the function "apply" instead of a "for loop", particularly for a function with multiple entries. I have a big data file and would like to apply a function in multi thread to accelerate the processus. I have a data frame containing values of* CO2 in ppm (resp[i,6])* that I want to convert in umol of CO2

#I would like to interpolate a straight line between 06/08/06 04:16:00 - 06/08/06 20:31:00 with values and then sum them. This is an estimate of ecosystem #respiration and I will be using this in a larger context(48 days of these diurnal curves), but for right now I am just trying to figure out how to do it for this one #day example. I have some other code for Ecosystem (stream) Metabolism that

I'm running an ANOVA on some data for respiration in a forest. I am having a problem with my degrees of freedom. For one of my variables I get one fewer degrees of freedom than I should. I have 12 plots and I therefore expected 11 degrees of freedom, but instead I got 10. Any ideas? I have some code and output below: > class(Combined.Plot) [1] "character" >

I am working with a dissolved oxygen dataset. continuous readings are taken at 15 minute intervals and we have been recording these data at 12 stations along the savannah river for two years now. The longest set of readings that are continuous without interuption is 53 days. I would like to look at the power spectral density at each of these sites (most likely one day will be the overridding

I am trying to run an ANOVA on my soil respiration data, but I keep getting residual sum of squares and mean square of zero. As I understand it that would mean that the model terms explain all of the variation in the response variable. That should be virtually impossible, should it not? Where do I begin troubleshooting such a problem? -- View this message in context:

odfWeave is throwing up a cryptic error, after successfully processing a file with a large number of figures (~30) and many \Sexpr{} calls. The error is (at least to me) cryptic. I am not sure where to look to correct this problem. Here's the error: Post-processing the contents Error in .Call("RS_XML_Parse", file, handlers, endElementHandlers, as.logical(addContext), :

Hello all, I would like to do a Dunnett test in glht(). However, the factor level I want to use as the control is not the first. dunn1<-glht(model3, linfct = mcp(Container = "Dunnett"), alternative = "less") The factor container has 8 levels, so it would be nice not to manually enter in all of the contrasts. I originally discovered glht() when working with a glm model

Dear List, After running a compound symmetric model using gls, I realized that the default contrasts were not the ones that made the most sense given the biological relationships among the factor levels. When I either changed the factor levels to re-arrange the order they occur in the gls model (not shown below) OR specifically change the contrasts I get the exact same estimates for the

Hi All I was wondering how to get the same results with gls and lme. In my lme, the design matrix for the random effects is (should be) a identity matrix and therefore G should add up with R to produce the R matrix that gls would report (V=ZGZ'+R). Added complexity is that I have 3 levels, so I have R, G and say H (V=WHW'+ZGZ'+R). The lme is giving me the correct results, I am

Hello everybody! I?m working with a dataset from eleven field trails on barley fertilization. I use R 1.6.2 (Windows) It is quite easy to fit aov() objects to the dataset. The call: > (l1t4y.aov <- aov(Yield ~ Trial + Treatment, data=led1t4b)) Results in an object with this anova table: Df Sum Sq Mean Sq F value Pr(>F) Trial 10 121423585 12142358 63.499