bootstrap {asbio} | R Documentation |
The function serves as a simplified alternative to the function boot
from the library boot
.
bootstrap(data, statistic, R, matrix = FALSE)
data |
Raw data to be bootstrapped. A vector or quantitative data or a matrix if matrix =TRUE . |
statistic |
A function whose output is a statistic (e.g. a sample mean). The function must have only one argument, a call to data. |
R |
The number of bootstrap iterations. |
matrix |
A logical statement. If matrix = TRUE then rows in the matrix are sampled as multivariate observations. |
With bootstrapping we sample with replacement from a dataset of size n with n samples R
times. At each of the R
iterations a statistical summary can be created resulting in a bootstrap distribution of statistics.
Returns a bootstrap distribution of a statistic.
Ken Aho
Manly, B. F. J. (1997) Randomization and Monte Carlo methods in biology, 2nd edition. Chapman and Hall, London.
library(vegan) data(varespec) site18<-data.frame(t(varespec[1,][1:20]))# A partial set of observations from a single plot for a Scandinavian moss/vascular plant/lichen survey. #Shannon-Weiner diversity SW<-function(data){ d<-data[data!=0] p<-d/sum(d) -1*sum(p*log(p)) } bootstrap(site18[,1],SW,R=1000,matrix=FALSE)