similar to: Nested design

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

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

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

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

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

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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

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, I am having a problem specifying the correlation structure in lme which leads to the error: Error in getCovariate.corSpatial(object, data = data) : Cannot have zero distances in "corSpatial". I have specified a grouping variable which is the only fix I could find by searching this error on R-help. ISee the below example. When my samples (tran) - which are transects

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 =

Hello, I have the following design, counts were collected at different transects, different depths and different sites at different times. Time is continuous and assumed to be random, all the others are categorical fixed where transect is nested within depth which is nested within site. I would like an expert opinion about the following code where intercept is modeled as random (I am not sure

Dear listers, I am trying to assess variance components for a nested, mixed-effects model. I think I got an answer that make sense from R, but I have a warning message and I wanted to check that what I am looking at is actually what I need: my data are organized as transects within stations, stations within habitats, habitats within lagoons. lagoons: random, habitats: fixed the question is:

I'd greatly appreciate your help in making a bar graph with multiple variables plotted on it. All the help sites I've seen so far only plot 1 variable on the y-axis Data set: I have 6 sites, each measured 5 times over the past year. During each sampling time, I counted the occurrences of different benthic components (coral, dead coral, sand, etc.) over 5 transects in each site site

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

Is there a package, or does anyone have code they are willing to share, that would allow me to simulate sampling of dead wood pieces across an area? I am specifically looking for code to simulate the dead wood distribution as small line segments across an extent, and then I will "sample" the dead wood using different sampling techniques including line transects, fixed area plots, etc.

Dear all, I am analyzing counts of seabirds made from line transects at sea. I have been fitting Poisson and negative binomial distributions to the data using the goodfit function from the vcd library. I would also like to evaluate how well a quasi-poisson distribution fits the data. However, none of the potentially suitable functions I have identified (goodfit(vcd), fitdistr(MASS),

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

Greetings This is a long email. I'm struggling with a data set comprising 2,278 hydroacoustic estimates of fish biomass density made along line transects in two lakes (lakes Michigan and Huron, three years in each lake). The data represent lakewide surveys in each year and each data point represents the estimate for a horizontal interval 1 km in length. I'm interested in comparing