similar to: expert opinion on lmer

Hi I got the following error using as.xts Error in xts(x, order.by = order.by, frequency = frequency, ...) : NROW(x) must match length(order.by) Here is how the data looks like > d1 <- read.csv(file.path(dataDir,"AppendixA-FishCountsTable-2009.csv"), as.is=T) > d1[1:3,] dive_id date time species count size site depth level TRANSECT VIS_M 1 62 10/12/2009

Hello, I have the following loop for two data sets: diveData_2008 and diveData_2009. It uses two other data: diveCond_all and fishTable. The problem is at the point to identify the dive_id for the given index (index is timestamp). It keeps on saying for the1st loop Error in fishReport$dive_id[i] <- dive_id : replacement has length zero for the 2nd loop Error in fishReport$dive_id[i + j] <-

Dear R Community! We analyse the impact of climbing activity on cliff vegetation. During our fieldwork, we recorded 90 Transects in 3 climbing sites. The aim is to see, if the plant cover (response: Cover) is influenced only by crevice availability (predictor: Cracs), or, additional, by the distance to the climbing route (predictor: Distance). Six plots are nested within one Transect

Hello, I looked in the R-help but could not find an archive addressing the following. I would like to convert a character to numeric after reading a file with RDS extension. After using as.numeric, I checked if it is numeric. It was not converted. Please help. Here is my code >Report <- readRDS(file="RDS/Report.RDS") > Report[1:2,] dive_id date

Dear R friends, I have a matrix with 2060 rows and 41 columns. One column is Date, another is Transect, and another is Segment. I want to ensure that there are 9 Transects (1 to 9) for each Date, and 8 Segments (1 to 8) for each Transect in the matrix, by inserting rows where these are missing. I am new to coding, but am trying to write a loop which checks if each of the transects already

# I need to create an xyplot() where I control the specific order of # both my conditioning variables. The default code below plots the # data correctly (dispersed across all 14 columns), but fails in two # ways. Both the primary conditioning variable (Transect), and the # secondary conditioning variable (Offset) are in alphanumeric order, # rather than the specific order I need. # Here

Due to an error on my part, I have renamed the previously attached file from T_5-04b_LTC-SE-SO-Compared.csv to T_5-04b_LTC-SE-SO-Compared.txt. It remains a comma-delimited file so the extension can be changed and used per the script, or loaded separately. My sincere apologies, Guy -----Original Message----- From: Guy Jett Sent: Friday, March 18, 2011 1:13 PM To: 'r-help at

Hello everybody, In am trying to analyse a BACI experiment and I really want to do it with R (which I find really exciting). So, before moving on I though it would be a good idea to repeat some known experiments which are quite similar to my own. I tried to reproduce 2 published examples but without much success. The first one in particular is a published dataset analysed with SAS by

Hi, Here is my data, the first 10 rows > u=regCond_all[1:10,] > dput(u) structure(c(999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 1.9, 2, 1.97, 1.99, 1.83, 1.78, 1.6, 1.52, 1.52, 1.36, 10.53, 9.88, 9.88, 10.53, 10.53, 10.53, 5.26, 9.88, 10.53, 10.53, 5.4, 5.57, 5.46, 5.34, 5.5, 5.59, 5.62, 5.76, 6.23, 6.19,

Hi list. I'm trying to plot a graph "by" factors. Exactly, the x axis are my depths (as.factor), my left y axis are my transects (also as.factor) and I want to plot the mean and standard deviation (three samples per factor combination) of my SW (numeric) variable. The second y axis (at the right) will, probably, need to be displayed several times (for both left y axis

Hello, I would like to convert date as a factor to represent time in a repeated measure situation in the following code. How would I do that? > d <- read.csv(file.path(dataDir,"data.csv"), as.is=T,stringsAsFactors = FALSE) > d[1:2,] id date a b c y 1 1 8/6/2008 Red 15 B 22 2 1 8/6/2008 Green 15 B

Hi list members. I’ll try to plot the abundance means of nine transects as lines, with five points on each transect (A to I). I will also need to plot for each point, it’s standard deviation (once each point will have tree replicates) as whiskers. Another problem will be that all the points should exist for each transect, but we know that six of the nine transects will have blanks (A1, A2, A3, -,

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

Hi again. Perhaps a simple question this time.... I am analysing data with a dependent variable of insect counts, a fixed effect of site and two random effects, day, which is the same set of 10 days for each site, and then transect, which is nested within site (5 each). I am trying to fit the cross classified model using GLMM in lme4. I have, for potential use, created a second coding

Hi, We are analizing the relationship between the abundance of groupers in line transects and some variables. We are using the quasipoisson distribution. Do we need to include the length of the transects as an offset if they all have the same length?? Also, can we include in the gam models variables that are measured at different spatial scales? We have done an analysis to see what variables

Hi, I wonder if someone can help me. I have built a gam model to predict the presence of cold water corals and am now trying to evaluate my model by splitting my dataset into training/test datasets. In an ideal world I would use the sample() function to randomly select rows of data for me so for example with 936 rows of data in my HH dataset I might say ss <- sample(nrow(HH), size =

Dear R-users, I have the following problem. I have performed an experiment for which I gathered a lot of data which I now want to test. The problem is that I cannot find an appropriate test in R (I am a starter) and someone might give me a hand. This is what I have done: Across three sites (Site), I have laid out five transects (Trans)...meaning five transects in each sites. In each transect I

Dear R users, I am using lme and nlme to account for spatially correlated errors as random effects. My basic question is about being able to correct F, p, R2 and parameters of models that do not take into account the nature of such errors using gls, glm or nlm and replace them for new F, p, R2 and parameters using lme and nlme as random effects. I am studying distribution patterns of 50 tree

Hello, This should be pretty simple but I cannot get it right. Please point to the right code. Thanks. > last <- read.csv(file.path(dataDir,"plot1.csv"), as.is=T,stringsAsFactors = FALSE) > last date r_wvht 1 8/6/2008 0.9766667 2 8/8/2008 0.7733333 3 8/11/2008 1.4833333 4 8/13/2008 1.5766667 5 8/14/2008 1.3900000 6 8/18/2008 0.7800000 7 8/20/2008

Dear all, I am trying to calculate some measure of the amount of variability in the response variable that is explained by a model fitted in lmer m1<-lmer(response-var ~ Condition+(1|Site/Area/Transect),family="binomial") . I've seen from the literature that the precentage of explained deviance is a common measure. How can I calculate it? Thanks a lot for your help, I hope this