similar to: mixed effects models with nested factors

Buenos días, He cambiado la versión de R como siempre a través de: install.packages("installr") library(installr) updateR() En esta ocasión trabajando bajo windows 10. La versión 3.2.2 me ofrece menos mirror, pero mi principal problema es que no soy capaz de trabajar con Rcommander (ahora lo hago con RStudio) me da la siguiente salida: > utils:::menuInstallPkgs() --- Please select a

Dear All, I am analysing a dataset on levels of herbivory in seedlings in an experimental setup in a rainforest. I have seven classes/categories of seedling damage/herbivory that I want to analyse, modelling each separately. There are twenty maternal trees, with eight groups of seedlings around each. Each tree has a TreeID, which I use as the random effect (blocking factor). There are two

Hello everyone. Let me first begin by explaining what I'm trying to do... I have a calling card that has an access number and requires a PIN to be entered and then the number you want to dial, like normal calling cards. So what I have done is assign a local DID which when called, initiates a Dial to the access number of the calling card. Now, I'm having a hard time figuring out how to

Hi there, I've looked through the very helpful advice about adding fitted lines to plots in the r-help archive, and can't find a post where someone has offered a solution for my specific problem. I need to plot logistic regression fits from three differently-sized data subsets on a plot of the entire dataset. A description and code are below: I have an unbalanced dataset

Hi, I'm new to R and GLMMs, and I've been unable to find the answers to my questions by trawling through the R help archives. I'm hoping someone here can help me. I'm running an analysis on Seedling survival (count data=Poisson distribution) on restoration sites, and my main interest is in determining whether the Nutrients (N) and water absorbing polymer Gel (G) additions to the

Hi All, I am trying to do a survivorship analysis with library(survival)from a data set that looks like this: I followed a bunch of naturally germinated seedlings of an annual plant from germination to death (none made it to reproduce, and died in a period of ~60 days after germination.) I also know the size of the seed of every individual censused. So I am trying to analyze seedling survival as

Hello, I am trying to use the projection.matrix( ) function and am following the example given. I have my data formatted very similar to the test.census example. > str(AsMi05mat) `data.frame': 1854 obs. of 6 variables: $ Tag : num 501 502 503 504 505 506 507 508 509 510 ... $ Year : int 1995 1995 1995 1995 1995 1995 1995 1995 1995 1995 ... $ Length : num 34

Hola Jorge: Disculpa la tardanza pero me han tenido liado en otros menesteres. Yo no soy ni muchísimo menos un experto ni en series temporales ni en R de hecho retomo el tema después de muchos (demasiados) años aparcado y dedicándome a labores de programación pura y dura. Respecto a la diferencia de resultados con R y Statgraphics, no conozco el proceso de selección del modelo ARIMA que hace

Dear all I was trying to put a title for my plot, but i got this result, > x11(width=10,height=5,title="seedling");par(mfrow=c(1,2))Error in x11(width = 10, height = 5, title = "seedling") : unused argument(s) (title = "seedling")> The title is not taking How can i give a title for the plot (where in need to make 2 plots within a window of x11() ) thanking

Dear R gurus, I have XY data giving the locations of tree seedlings that were surveyed during a 210 meter belt transect. This belt transect was taken by stretching a line across the field, then measuring all seedlings within 1 meter on either side of the line. The end result was XY coordinates and height for ~1,300 seedlings. I would like to use that data to calculate density of

Full_Name: Charles J. Geyer Version: 1.8.0 OS: i686-pc-linux-gnu (Suse 8.2) Submission from: (NULL) (134.84.86.22) Two bugs (perhaps related, perhaps independent) revealed by the same Poisson regression with offset mydata <- read.table(url("http://www.stat.umn.edu/geyer/5931/mle/seeds.txt")) out.fubar <- glm(seedlings ~ burn01 + vegtype * burn02 + offset(log(totalseeds)),

Hi all, I am trying to run a glm with mixed effects. My response variable is number of seedlings emerging; my fixed effects are the tree species and distance from the tree (in two classes - near and far).; my random effect is the individual tree itself (here called Plot). The command I've used is: mod <- glmer(number ~ Species + distance + offset(area) + (1|Plot), family = poisson)

Hello, After putting together interaction code that worked for a single pair of interactions, when I try to evaluate two pairs of interactions( flowers*gopher, flowers*rockiness) my computer runs out of memory, and the larger desktop I use just doesn't go anywhere after about 20 minutes. Is it really that big a calculation? to start: mle2(minuslogl = Lily_sum$seedlings ~ dnbinom(mu = a,

Could someone explain the meaming of this error message from augPred: > augPred(area3.pen.nlme, primary=~day) Error in predict.nlme(object, value[1:(nrow(value)/nL), , drop = FALSE], : Levels 1,2,3 not allowed for block > predict.nlme(area3.pen.nlme) does not produce an error. area3.pen.nlme was created with: > area3.pen.nlme <- nlme(area ~ SSlogis(day, Asym, xmid, scal),

Dear R users, I have been having problems getting believable estimates from anova on a model fit from lmer. I get the impression that F is being greatly underestimated, as can be seen by running the example I have given below. First an explanation of what I'm trying to do. I am trying to fit a glmm with binomial errors to some data. The experiment involves 10 shadehouses, divided between

Hi, I ran the example on pp. 799-800 from Machael Crawley's "The R Book" using package survival v. 2.36-5, R 2.13.0 and RStudio 0.94.83. The model is a Cox's Proportional Hazards model. The result was quite different compared to the R Book. I have compared my code to the code in the book but can not find any differences in the function call. My results are attached as well as a

dear allI have a data set with three types (Tree, Sapling, Seedling). I have estimated the correlation values. now i need to bring all the correlation values in a table like the one i have shown in attached file with R codes.could you please give me idea on this problem thanking you MSNepal _________________________________________________________________ Hotmail: Trusted email with

Hi all, I have played a bit with the "reshape" package and function along with "melt" and "cast", but I feel I still don't have a good handle on how to use them efficiently. Below I have included a application of "reshape" that is rather clunky and I'm hoping someone can offer advice on how to use reshape (or melt/cast) more efficiently. #For this

hello, i try to plot 3 graphs which have the same x.axis underneath each other. i'd like the plots to be aligned without margings between the boxes and draw a single x axis beneath the lowest plot. i managed to get the alignment by setting par(mar), but the middle box is stretched and i cant't figure out how to get around this. par(pin) was my guess, but this doesn't do the job

Estimados R-users: Estoy intentando usar la función 'agrep' para hacer búsquedas en cadenas de texto. El parámetro max.distance permite controlar la medida de aproximación de búsqueda de la función de Levenshtein. No obstante, cuando hago búsquedas específicas no obtengo siempre el resultado deseado y no se si es un bug o que no entiendo bien el algoritmo de búsqueda. Por