similar to: Generating repeated network measures in R

Hi, I have a experiment with block, plots, sub-plots, and sub-sub-plots with repeated measures and 3 factors (factorial design) when we have been observed diameter (mm), high (cm) and leaves number (count). However, we don't have one treatment in one factor, so, my design is unbalanced. On a previous message here, a friend tell me that "It appears to me that your design is a split-split

Dear all, I am trying to analyze data from an experiment like this: Factors: Hormone - Levels: SH, CH (S = without; C=with; H=Hormone) Time - Levels: 19/08/09, 04/09/09, 18/09/09, 08/10/09, 20/10/09 (DD/MM/YY) Nutrition - Levels: Completa, Sem (without) Macronutrition - Levels: Ca, K, Mg, P, Sem (without) Time is the measures day. It reflect the days after germination. Blocks : 4 plants per

Dear list member, My question is related to input file format to an Anova from car package. Here is an example of what I did: My file format is like this (and I dislike the idea that I will need to recode it): Hormone day Block Treatment Plant Diameter High N.Leaves SH 23 1 1 1 3.19 25.3 2 SH 23 1 1 2 3.42 5.5 1 SH 23 1 2 1 2.19 5.2 2 SH 23 1 2 2 2.17 7.6 2 CH 23 1 1 1 3.64 6.5 2 CH 23 1 1 2

I am trying to define groupings from levels of factor variables and this the warning message that R give "& not meaningful for factors". The nature of my task is this. I have a variable stage which has the levels (1B, 2A, 2B) - these are the AJCC TNM stages of cancer, and another variable diameter with factor levels ("=< 4", "4 - 6.5, > 6.5; limit values are

Hi, I have a function that generates a set of data but I am having problems determining the parameters using the nls fitting procedure. #### "MH"<-function(field,diameter,mu=10e-7,sig=0.1,Ms=100,chi=0){ #variables mu, sig, chi, Ms #input: field and diameter #all in CGS rho <- 5 kb <- 1.38e-16 t <- 300 length.d<-length(diameter) length.H<-length(field)

For a variety of displays (mosaicplots, barplots, ...) one often wants to either abbreviate or wrap long labels, particularly when these are made up of several words. In general, it would be nice to have a function, abbreviate.or.wrap <- function(x, maxlength=10, maxlines=2, split=" ") { } that would take a character vector or a list of vectors, x, and try to abbreviate or wrap

I received at least one email suggesting a Windows-based rendering farm - likely to consist of a few rack systems all running 64-bit Windows. I read an article on Tomshardware which gave some decent insight. What can list participants offer on this concept? I don't care _how_ the resource is implemented - virtual machine, cluster, etc. I just want to get the most resources for the money,

Hi ilai Thank you for your suggestions. I do not know what happened yesterday I must have omitted a few changes out in going from R to email and apologies for the double posting - I had troubles sending it as my ISP gave a message of not being connected for email but was for the web I was trying to get panel.Locfit to work in a number of situations. 1. Conditioned by Farm (3 panels) with 2

Dear list I'm trying to solve the following problem since 2 days with no success. Could someone help a newbie, please ? I have a dependant variable which is diameter of shell, and two factors which are level on the beach (3 levels 'B', 'E' and 'H') and a hydrodynamics indice (3 levels 1, 2 and 3) To study diameter variations according to these factors, I may use

Hi, Maybe this is more a programming questions than a specific R-project question, but maybe there is someone who can point me in the right direction. I have a picture of cirkels which I took with a digital camera. Now I want to use the diameter of the cirkels on the picture for analysis in R. I can use pixmap to import the picture, but how do I find the outside cirkels and calculate the

Dear all, The 'make check' step fails for the pacakge mva on IBM AIX. The tail of the Rout log file looks like: > for(factors in 2:4) print(update(Harman23.FA, factors = factors)) Call: factanal(factors = factors, covmat = Harman23.cor) Uniquenesses: height arm.span forearm lower.leg weight 0.170 0.107 0.166

I can not figure out what the heck is going on. I went back to my old version and I still get errors when the voicemail system tries to load any of the greetings, unavail messages, etc. the normal voicemail prompts work, but any user recording don't work. Leaving a new message appears to work, but the system wont replay them, it throws errors. Here is an example of the errors: Oct 11

Greetings, I'm running v3.3.0 on Fedora16-x86_64. I used to have a replicated volume on two bricks. This morning I deleted it successfully: ######## [root at farm-ljf0 ~]# gluster volume stop gv0 Stopping volume will make its data inaccessible. Do you want to continue? (y/n) y Stopping volume gv0 has been successful [root at farm-ljf0 ~]# gluster volume delete gv0 Deleting volume will erase

I have a data set with the following structure (with many more obs.): var1 expt day diameter 1 1 2 0.5 1 1 3 0.9 1 1 4 1.3 1 1 5 1.7 1 2 2 0.3 1 2 3 0.5 1 2 4 0.9 1 2 5 1.6 2 1 2 0.7 2 1 3 1.2 2 1 4 1.6 2 1 5 2.3 2 2 2 0.4 2 2 3 0.8 2 2 4 1.6 2 2 5 3.2 I can get separate regression analysis for each level of var1 and expt with the command: by(data3, data3$var1:data3$expt, function(x)

Hello everyone. There is a new competition, outlined on the blog dataists<http://www.dataists.com/2010/10/using-data-tools-to-find-data-tools-the-yo-dawg-of-data-hacking/>, inviting us to analyse statistics of the use of R packages (collected from 52 R users), to create a R-package suggestion engine for ourselves. Since I noticed several bloggers already wrote about it (as I have detailed

Hello, I want to fit a Gompertz model for tree diameter growth that depends on a 4 levels edaphic factor (?Drain?) and I don?t manage to introduce the factor variable in the formula. Dinc is the annual diameter increment and D is the Diameter. >treestab > Dinc D Drain [1,] 0.03 26.10 2 [2,] 0.04 13.05 1 [3,] 0.00 24.83 1 [4,] 0.00 15.92 4

I'm experiencing some confusion with the ellipsis argument (...). In my .Rprofile, I have the following functions: stderr <- function(x, ...) { sqrt( var(x, ...) / length(x) ) } se <- stderr I can use tapply to calculate some means: > tapply( Diameter, factor(Region), mean, na.rm=TRUE ) I II III IV V 0.02896429

I am looking a risk factors for disease in cattle and am interested in modelling farm and sampling cluster as random effects (My outcome is positive or negative at the level of the farm). I am using R version 2.0.1 on a Mac and have identified glmmPQL as hopefully the correct function to use. I have run a couple of models using this but was hoping that you might be able to answer a few questions.

Hi all, I would like to test the homoegeneity of variances between several linear model for some analysis of covariance. It seems that the Bartlett's test is a good test to use but I am having problem using with linear model and I cannot find any examples on the internet. There are some examples for comparisons of variances but not linear models. If I take the hellung data set, which is

hi! I apologize in advance if this is a newbie dumm question, but I really can't figure it ou. I have lists of sumeric and character data on some URLs, which look like this: <photo id="5876248819" owner="13716719 at N04" secret="faf9bb7f52" server="5264" farm="6" title="our rose garden" ispublic="1"