search for: grazed

Hi, Try either: res1 <- apply(mydata[,1:2],2,mean) ?res2 <- colMeans(mydata[,1:2]) ?identical(res1,res2) #[1] TRUE # Also if you need to find means for each group ("Ungrazed vs. "Grazed") by(mydata[,-3],mydata[,3],colMeans) #or if column names are "V1", "V2", "V3" aggregate(.~V3,mydata,mean) #or library(plyr) ?ddply(mydata,.(V3),numcolwise(mean)) A.K. I have a data set with two columns of data that I want to find the mean of...

Hi everyone! I have a simple model that i would like to plot with 95% CIs. It is like follows: m1<-lmer(Richness~Grazing+I(Grazing^2)+(1|Plot),family=poisson) By using the effects package I get two plots, one for the linear term and one for the squared term. Q1: Can I get all in one? I.e. with one line for the whole model? Q2: Can I also visualize the random effects? I would be very happy for

Dear R- Community, to learn i reanalysed some data provided and analysed by Zuur et. al. in their book "Mixed effect models and Extensions in Ecology with R". When i run the last command i get a warning message i dont understand. Loyn<- read.table(file = "loyn.txt",header = TRUE) Loyn$L.AREA<- log10(Loyn$AREA) fGRAZE <-factor(Loyn$GRAZE) M0<- lm(ABUND~ L.AREA

Good afternoon My name is Joanne Lenehan, I am a post grad at UNE using R version 2.9.0 I came across the Tweedie package in old R help posts and was interested in giving it a go for some data. The data is below and also attached as BaregroundLitterLogs Site Treatment Graze Dam Plot Time Bare Litter Logs 1 C remote yes 1 A 0 2 0 1 C remote yes 2 A 0 15 0 1 HE

Hi, For my master thesis I have 24 micro-plots on which I did measurements during 3 months. The measurements were: - Rainfall and runoff events throughout 3monts (runoff being dependant on the rainfall, a coefficient (%) has been made per rainfall event and per 3 months) - Soil texture (3 different textures were differentiated) - Slope (3 classes of slopes) - Stoniness (one time measurement)

I have a two part question one about statistical theory and the other about implementations in R. Thank you for all help in advance. (1) Am I correct in understanding that Heteroscedasticity is a problem for Generalized Additive Models as it is for standard linear models? I am asking particularly about the GAMs as implemented in the mgcv package. Based upon my online search it seems that some

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 all, I am a new member to the list - and to the analysis that I am attempting. I have the following case A group of us have been monitoring (over a period of a few years) a number of paired plots that were flooded and / or burnt. The plots are located in two topographical settings, some were burnt, some were flooded, some were burnt & flooded and some were not affected at all. At

...gnostic code below model4<-glm(Biomass~(Treatment+Time+Site)^2, data=bobB, family=quasi(link="log", variance="mu")) par(mfrow=c(2,2)) plot(model2) to test the effect of grazing exclusion of feral horses for a Phd with following factors: Treatment - 3 levels which are grazed controls (C), ungrazed horse exclosures (H)with 3 wire strand fence to allow other herbivores but not horses and ungrazed full netting exclosures to exclude all herbivores (A) Site - 6 levels for 6 Sites which are considered fixed Time - 6 levels also for 6 different monitoring or time periods w...

...in permutest(). More precisely I have dependence in my data that should be allowed for in the permutation - I simulated the problem in the example of the vegan documentation p.24: library(vegan) data(varespec) ## Bray-Curtis distances between samples dis <- vegdist(varespec) ## First 16 sites grazed, remaining 8 sites ungrazed groups <- factor(c(rep(1,16), rep(2,8)), labels = c("grazed","ungrazed")) ## Calculate multivariate dispersions mod <- betadisper(dis, groups) ## Perform test anova(mod) ##simulation of dependence; blocks blocks<-factor(c(rep(1,4),rep(2,4)...

...gnostic code below model4<-glm(Biomass~(Treatment+Time+Site)^2, data=bobB, family=quasi(link="log", variance="mu")) par(mfrow=c(2,2)) plot(model2) to test the effect of grazing exclusion of feral horses for a Phd with following factors: Treatment - 3 levels which are grazed controls (C), ungrazed horse exclosures (H)with 3 wire strand fence to allow other herbivores but not horses and ungrazed full netting exclosures to exclude all herbivores (A) Site - 6 levels for 6 Sites which are considered fixed Time - 6 levels also for 6 different monitoring or time periods w...

Hello, I would appreciate if somebody could help me clear my mind about the below issues. I have a factorial experiment to study the effects of Grazing and Fire on Forest biomass production. The experimental unit (to which the treatment combinations are applied) are PLOTs. The measures were made repeatedly for 13 years. I am planning to use the linear mixed effect model function lme in R for this.

Hello all, My question is how do I write a multilevel regression model of individual responses to environmental predictors that accounts for social interactions between individuals. i.e.; 1) Individual response is nested within a group response. 2) The same environmental predictors apply to both hierarchical levels but, 3) Lower level slope/intercept are also affected by high-level response.

A rather strange situation here and I've not found the source of the problem. The point is to print a ternary plot matrix of compositional data with ellipses enclosing 95% of the variance in each plot. The ellipses display on the monitor, dev = x11cairo (see attached winters-x11cairo.pdf), but not when sent directly to a file, dev = pdf (see attached winters-pdf.pdf). Here's

Heya, i got this problem with stubborn win98 machine refusing to show up on the browse list, my samba is the local/domain master browser and login server for the whole local network, using user security. the workstation has all the same protocols and settings like the other 6, only difference is the ip and the netbios name, the login used on that machine matches existing username on my linux

...e.dist <- vegdist(wisconsin(varespec)) library(MASS) ## isoMDS mds.null <- isoMDS(vare.dist, tol=1e-7) mds.alt <- isoMDS(vare.dist, initMDS(vare.dist), maxit=200, tol=1e-7) vare.proc <- procrustes(mds.alt, mds.null) vare.proc groups <- factor(c(rep(1,16), rep(2,8)), labels = c("grazed","ungrazed")) source("xyplot.procrustes.R") xyplot(vare.proc, y ~ x | groups, data = as.data.frame(groups), kind = 1) The resulting plot has too many arrows on each panel - some points have multiple arrows emanating from they. panel.procrustes() is defined as: `panel.proc...

hi,all I want set up a puppet HA structure. but if the puppetd can set more than one server address ,the work will be simple :D if one puppetmaster have error, the client can auto try the next. I think I can use the heartbeat or dns to do this same thing,but not so good. so I want know the puppetd can direct set in the configure file ? if not,will be add this option? -- Huang

All, I'm having a problem with an Innomedia 6328-2Re (old Sunrocket Gizmo). It keeps losing registration after a period of time ranging from a few minutes to a few hours. It seems that right before it loses registration, it fails to send a second register (after the 401 unauthorized). Here's a transcript from wireshark (at the end). The last message is all that's received and

All, I've migrated a share from an older samba server (3.0.33) running on a Sun Solaris box to a newer samba server (3.6.23) running on a RedHat Linux 6 box. For the most part I've tried to keep the configuration the same (simply to make the migration easier since I'm not an expert on Samba config options). I got the authentication working (security=domain) but now I'm