Hello List,

This is Elaine.
I am running betadiver for a dataset of 4873 rows and 2749 columns.
(4873 rows = 4873 gridcell of the study region and 2749 columns for the
bird species)
The dataset was produced by combing 5 dbf.

When running the code o, an error message jumped out, saying
"Error: cannot allocate vector of size 90.6 Mb"

I posted the issue in r-help and checked the previous mails about R memory
problems.
gc() and save .Rdata were tried but did not work.
Also, I tried to transformed the dataset into a matrix, using the code m
below.
However, an error also appeared, saying
"Error in ifelse(x > 0, 1, 0) :
  (list) object cannot be coerced to type 'double'."

Please kindly advise how to alleviate the memory problem, particularly in
modifying the code of betadiver of vegan.
Thank you.

Elaine

code m
matrixR<-matrix(data = dataR, nrow = 4873, ncol = 2749)
d  <-  betadiver(matrixR,  "sim")



code o
# Non-Passerine table
dataNP_1 <-read.dbf("H:/temp_D/stage_4_R_2748/NP_1-10.dbf", as.is = FALSE)
dataNP_2 <-read.dbf("H:/temp_D/stage_4_R_2748/NP_11-19.dbf", as.is = FALSE)
dataNP<-merge(dataNP_1,dataNP_2,by=c("GID"),all=T)

.. skip...

# Non-Passerine and Passerine table (2748 species)
dataR<-merge(dataP,dataNP,by=c("GID"),all=T)
dim(dataR)
str(dataR)

library(vegan)

  ##  The  beta sim  index (Lennon 2001)
  d  <-  betadiver(dataR,  "sim")

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