Hi Aaron,
try the argument "statistic=mean". Then boot() will give you the mean
turn angle in your actual data (which appears to be 6 degrees, judging
from what you write), as well as the means of the bootstrapped data.
Then you can get (nonparametric) bootstrap CIs by
quantile(boot$t,probs=c(.025,.975)). As far as I can see, there is
really no need to look at sd().
A more interesting question would be how to deal with the fact that
-180=+180, there may be something to think about here...
HTH,
Stephan
aaron.fo...@students.tamuk.edu schrieb:
Hi All,
I'm new to R so please bear with me. I have a dataset with 337 turn angles
ranging from -180 to 180 degrees. I need to bootstrap (sample with replacement)
1,000 times to create expected average turn angle with 95% CIs. The code is
pretty straightforward (<-boot(data =, statistic = ,R =)) but I am unsure how
to input my observed mean (6 degrees) and standard deviation (66 degrees) into the
statistic component. I realize there is a 'function' code but I can't seem to
carry the results over to the 'boot' code.
Thanks,
Aaron M. Foley
PhD Candidate
Caesar Kleberg Wildlife Research Institute
Texas A&M University - Kingsville
Cousins Hall, Room 201
Kingsville, TX 78363
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