similar to: doing zero inflated glmm for count data with fmr

Dear all, I would like to conduct a Pearson's correlation using cor.test separately for each individual in my data set. Each individual has nine observations of the measurement variable 'Delta13C'. I can figure our how to do it manually one 'Individual_ID' at a time, but I cannot figure out how to automate the process (a loop I am guessing). In addition, I would like to

Dear list, The below dataset and code creates a new dataset with the results from the function cor.test being performed on each individual ('Individual_ID') from my original dataset. How do I convert each variable from the cor.test results to a numeric data type, as it is passed into the new dataframe? For example, 'estimate', 'p.value', and 'conf.int' should be

Hello, I have a dataset with a continuous independent variable (fish length, range: 30-150 mm) and a binary response (foraging success, 0 or 1). I want to discretize fish length into 5 mm bins and give the proportion of individuals who successfully foraged in each each size bin. I have used the cut function to discretize the length values into my desired bins, but I can't figure out how to

Dear list, I have 9 repeated measures (measurement variable == 'Delta13C') for individuals (ID variable == 'Individual_ID'. Each repeated measure is "indexed" (right term?) by the variable 'FeatherPosition' and given as c('P1', 'P2', 'P3', 'P4', 'P5', 'P6', 'P7', 'P8', 'P9'). I would like to

I have a list of observations of individuals. I would like to make a list of individuals, with a data frame of observations for each individual. The following code usually works, but not always ---------------------------------------------------------------------- # Make a list of empty data frames animals = list() indivs = levels(Z$individual_id) donotprint <- sapply(indivs, function(i){

Hello all, If someone could take a little time to help me then I would be very grateful. I studied piping plovers last summer. I watched each chick within a brood for 5 minutes and recorded behaviour, habitat use and foraging rate. There were two Sites, the first with 4 broods and the second with 3 broods. http://r.789695.n4.nabble.com/file/n4511178/Table_PP_Maslo_et_al.png As the data within a

Dear list, I have a dataset where we sampled multiple individuals either 1 or 9 times. Our measurement variable is 'Delta13C' (see below sample dataset). I cannot figure out how to efficiently use a vector command (preferably) or a loop to create a new vector of the names of the individuals sampled 9 times. Note that the 'FeatherPosition' variable will only be "P1" for

Hi, Use offset variables if count occurrences of an event and you want to model the observation time. glm(count ~ predictors + offset(log(observation_time)), family=poisson) If you want to compare durations, look at library(survival), ?coxph If tnoise_sqrt is the square root of tourist noise, your example seems incorrect, because it is a predictor, not the dependent variable tnoise_sqrt ~

I am working with transition matrices of sequences of animal behaviours. What I would like to do is parse the original matrices, adjusting row/column order so that the matrix has its main values in blocks surrounding the diagonal. This would cause behaviours involved in functional groupings (e.g. grooming, resting, foraging etc) to appear as blocks. This can be done manually by applying

Hello Lets say as an example I have a dataframe with the following attributes: rownum(1:405), colnum(1:287), year(2000:2009), daily(rownum x colnum x year) and foragePotential (0:1, by 0.01). The data is actually stored in a netcdf file and I'm trying to provide a conceptual version of the data. Ok. I need to calculate a moving mean and a moving variance for each cell on the following

Hi All I am trying to translate a proc mixed into a lme() syntax. It seems that I was able to do it for part of the model, but a few things are still different. It is a 2-level bivariate model (some call it a pseudo-3-level model). PROC MIXED DATA=psdata.bivar COVTEST METHOD = ml; CLASS cluster_ID individual_id variable_id ; MODEL y = Dp Dq / SOLUTION NOINT; RANDOM Dp Dq / SUBJECT = cluster_ID

I'm stumped, can anyone find my error in this sequence. for(j in 1:(varsize[4]-1)) temp <- get.var.ncdf(nc=input, varid="p_foraging",c(1,1,j),c(varsize[1],varsize[2],1)) filled.contour(x, y, temp, color = terrain.colors, plot.title = title(main = paste("Everglades Wood Stork Foraging Potential \nYear", (2000+j)), xlab =

Dear R gurus I am analysing data from a study of behaviour and shade utilization of chimpanzees. I am using GLMs in R (version 2.13.0) to test whether shade/sun utilization is predicted by behaviour observed. I am thus interested in whether an interaction of behaviour (as a predictor) and presence in the sun/shade (also predictor) predicts the counts I have for the respective categories. I have

Hello all, I'm having difficulty with setting up a mixed model using lme in the nlme package. To summarize my study, I am testing for effects of ornamentation on foraging behavior of wolf spiders. I tested spiders at two different ages (penultimate vs. mature) and of two different phenotypes (one species tested lacks ornamentation throughout life [non-ornamented males] while the other

Hello, I really like the interface and flexibility of the ggplots package. However, I cannot find how to add text to a plot (like the 'text' and 'rect' functions in the graphics package). I will appreciate any suggestions. Thanks, Ofir. -- View this message in context: http://www.nabble.com/adding-text-and-other-elements-to-ggplot2-plots-tp22455395p22455395.html Sent from the R

Author: srust Repository: /hg/zfs-crypto/gate Revision: 4d540ed747f47f1138e3dad6a142ee9f24106c07 Log message: PSARC 2005/546 FMR Update for IBTF 6227237 IBCM blames the client for SM''s fault 6281147 ibtl does not support fast memory registration (FMR) 6334921 tavor needs to support fast memory registration 6337636 tavor should use MSIs when possible Files: update:

Author: hiremath Repository: /hg/zfs-crypto/gate Revision: b94c5adf07fad899514e6b3afca80b99eaf8cd7d Log message: PSARC 2006/026 IBTF FMR buf addition 6377680 ibt_map_mem_area() needs ability to map mem attributes via buf(9s) Files: update: usr/src/uts/common/sys/ib/ibtl/ibtl_types.h

Hi All, I'm trying to run a simulation of host-pathogen evolution based around individuals. What I need to have is a dataframe or table of some description - describing all the individuals of a pathogen population (so far I've implemented this as a matrix): ID No_of_Effectors Effectors (Sequences) [1,] 0001 3 ## 3

https://bugzilla.samba.org/show_bug.cgi?id=6061 Summary: [FMR]: Add an option to only delete files once they expire Product: rsync Version: 3.0.4 Platform: x86 OS/Version: Linux Status: NEW Severity: enhancement Priority: P3 Component: core AssignedTo: wayned@samba.org

https://bugzilla.samba.org/show_bug.cgi?id=6062 Summary: [FMR]: Add an option to terminate rsync after a specific time Product: rsync Version: 3.0.4 Platform: x86 OS/Version: Linux Status: NEW Severity: enhancement Priority: P3 Component: core AssignedTo: wayned@samba.org