similar to: repeated measures ANOVA - among group differences

Hello R Folks, I am new to R. I have been struggling to overlay a barchart with a xyplot together on one plot but did not get this worked out. Any help and idea are greatly appreciated. I attached R scripts for barchart and xyplot below and also data I used. What I am trying to do is just to put the barchart and xyplot together on one plot. Huapeng <<dispersal_infestation.csv>>

Hello everyone I'm a beginner in Stats and R, I'm using R 2.10.1. I need to create a multivariate qq plot, there is 8 variable group with each has 55 number of input. An example of what I did so far, just to get my point out: > data=read.csv(file.choose(),header=T) > data country village group av_expen P2ary_ed no_fisher 1 Cook Islands Aitutaki D

Hello All, Once again thanks for all of the help to date. I am climbing my R learning curve. I've got a few more questions that I hope I can get some guidance on though. I am not sure whether the etiquette is to break up multiple questions or not but I'll keep them together here for now as it may help put the questions in context despite the fact that the post may get a little long.

Hi, I try to compute circular means for a matrix with NAs, but the function "circ.mean" return only means for lines with complete values and do not accept "na.omit=T" or "na.rm=T", or "na.action=na.omit", or "na.fail=T". Also, I try to use "polar.plot" of the package poltrix with the same matrix, but angles are not display because of

I have been looking into both of these approaches to conducting a GLMM, and want to make sure I understand model specification in each. In particular - after looking at Bates' Rnews article and searching through the help archives, I am unclear on the specification of nested factors in lmer. Do the following statements specify the same mode within each approach? m1 = glmmPQL(RICH ~ ZONE,

I'm trying out a basic plot, but something about the way I subset my data leads to problems with the plot. Here is the first bit of my data set year,date,location,quadrat_juvenile,photo_location,photo_exists,genus,count,divers 2005,2005-04-30, 1 Fringing Reef,1, 1 Fringing Reef Coral Transect Pole 1-2 Quadrat 1,t,Acanthastrea,0,HP+MEM 2005,2005-04-30, 1 Fringing Reef,1, 1 Fringing Reef

I have a function (see below). This function has one object, ID. If I run the loops by themselves using a character value (ie,"VFFF1-7") instead of the function object, then the loops work fine. However, when I try to insert the character value via the function call, it doesn't work. I don't get an error, but the TotalCover.df dataframe does not update according to the loop

THANKS so very much for your help (previous and future!). I have a two follow-up questions. 1) You say that dispersion = 1 by definition ....dispersion changes from 1 to 13.5 when I go from binomial to quasibinomial....does this suggest that I should use the binomial? i.e., is the dispersion factor more important that the 2) Is there a cutoff for too much overdispersion - mine seems to be

Hello, I am trying to plot a quadratcount object over a ppp object in the spatstat package. I ultimately want to get something like this http://bg9.imslab.co.jp/Rhelp/R-2.4.0/src/library/spatstat/man/images/big_quadratcount_001.png http://bg9.imslab.co.jp/Rhelp/R-2.4.0/src/library/spatstat/man/images/big_quadratcount_001.png See

I have a function (see below). This function has one object, ID. If I run the loops by itself using a character value (ie,"VFFF1-7"), then the loops work fine. However, when I try to insert the character value via the function call, it doesn't work. I don't get an error, but the TotalCover.df dataframe does not update according to the loop criteria. Any obvious problems that

I realized that I may not have answered the question you were asking and that no one else has responded. I can across a similar problem and may have an answer to your question now. If you have both the wavelet coefficients and the scaling coefficients then create a fake sequence of the same length as the original and decompose that sequence using wd form wavethersh with the same wavelet family

I have a nested ANOVA, with a fixed factor "tmt" nested within "site" (random). There are missing values in the data set. aeucs, tmt and site have been defined as objects I have tried: model1=lme(aeucs~tmt,random=~1|tmt/site) I get the following error message Error in na.fail.default(list(aeucs = c(0.833333333, 1, 1, 1, 1, 1, 0.666666667, : missing values in object I

Hi R-listers, I am trying to make a trellis boxplot with the HSuccess (y-axis) in each Rayos (beach sections) (x-axis), for each Aeventexhumed (A, B, C) - nesting event. I am not able to do so and keep receiving: Error in eval(expr, envir, enclos) : object 'Rayos' not found Please advise, Jean require(plyr) resp <- read.csv("ABC Arribada R File Dec 12 Jean

Hi, I know there are older threads discussing the quadratcount function in spatstat. Unfortunately, I could not find a solution to my problem there. I'm analyzing a point pattern in an irregular polygonal window. Both the window (an entire country) and the points are projected using WGS84. When I do quadratcount with only one quadrat for the entire country it holds all my 154 points:

I'm using R for Mac OSX version 1.14 (2129) and the geoR package version 1.6-5 (the current version in the R repository). I'm running R in OS 10.4.6 on a Mac G4 iBook (933MHz, 640 MB DDR SDRAM). I searched the R archive and did not find a posting on this issue. I want to use the variog and variog4 functions of geoR to characterize the pattern of spatial autocorrelation of tree

Hi all, I am using quadratcount in spatstat to divide a window containing a point pattern into a grid of quadrats containing the intensity of points in each quadrat. My data is in UTM co-ordinates. My window is defined as follows: >p15<-ppp(x,y,window=owin(c(341710,342100),c(3126465,3126780)),marks=NUL L, checks=TRUE) Giving me a distance of 390m in the 'x' direction and 315m in

Is there any package or operation in R designed to conduct or facilitate Quadrat Variance analysis of spatial data? Any leads would be much appreciated as I have found very little in my searches thus far. Tyler -- View this message in context: http://www.nabble.com/Quadrat-Variance-analysis-tp22752517p22752517.html Sent from the R help mailing list archive at Nabble.com.

hello, i need to calculate ci's for each of 4 groups within a dataset, to be able to infere about differences in the variable "similarity". the problem is that data within groups is dependent, as assigned by the blocking-factor "site". my guess was to use a block bootstrap but samples within in these blocks / sites are not of same length. i was not able to find a method to

I have photographs of plots that look like so: http://r.789695.n4.nabble.com/file/n4631960/Untitled.jpg I need to divide it up so each circle has an equal area surrounding it. So into 20 equal segments, each of which contains a circle. Quadratcount is not sufficient because if I divide it up into 36 equal quadrats, some quadrats do not contain one of the circles. I'm not even sure how to

hello, i'd appreciate help with my glmer. i have a dependent which is an index (MH.index) ranging from 0-1. this index can also be considered as a propability. as i have a fixed factor (stage) and a nested random factor (site) i tried to model with glmer. i read that it's possible to use a quasibinomial distribution, for this kind of data, which i than actually did - but firstly (1)