bootstrapping
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.foley at 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 [[alternative HTML version deleted]]
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