statistics bootstrap - Bootstrapping multiple columns with R -

i'm relatively new @ r , i'm trying build function loop through columns in imported table , produce output consists of means , 95% confidence intervals. ideally should possible bootstrap columns different sample sizes, first iteration working. have sort-of works, can't way there. code looks like, sample data , output included:

#cdata<-read.csv(file.choose(),header=t)#read data selected file, works, commented out because data provided below #cdata #check imported data  #sample data #   wall nrpk cisc whsc lkwh ylpr #1    21    8    1    2    2    5 #2    57    9    3    1    0    1 #3    45    6    9    1    2    0 #4    17   10    2    0    3    0 #5    33    2    4    0    0    0 #6    41    4   13    1    0    0 #7    21    4    7    1    0    0 #8    32    7    1    7    6    0 #9     9    7    0    5    1    0 #10    9    4    1    0    0    0  x<-cdata[,c("wall","nrpk","lkwh","ylpr")] #only select relevant species  i<-nrow(x) #count number of rows bootstrapping  g<-ncol(x) #count number of columns iteration  #build bootstrapping function, works first column doesn't iterate  bootfun <- function(bootdata, reps) {    boot <- function(bootdata){      s1=sample(bootdata, size=i, replace=true)     ms1=mean(s1)     return(ms1)    } # single bootstrap    bootrep <- replicate(n=reps, boot(bootdata))    return(bootrep)  } #replicates bootstrap of "bootdata" "reps" number of times , outputs vector of results  cvr1 <- bootfun(x$ylpr,50000) #have unsuccessfully tried iterating location various ways (i.e. x[i]) cvrquantile<-quantile(cvr1,c(0.025,0.975)) cvrmean<-mean(cvr1) vec<-c(cvrmean,cvrquantile) #puts results suitable form output vecr<-sapply(vec,round,1) #rounds results vecr        2.5% 97.5%   28.5  19.4  38.1   #apply(x[1:g],2,bootfun) ##doesn't work in case  #desired output:  #species    mean lowerci upperci #wall       28.5    19.4      38.1 #nrpk       6.1 4.6    7.6 #ylpr       0.6 0.0    1.6 

i've tried using boot package, , works beautifully iterate through means can't same confidence intervals. "ordinary" code above has advantage can retrieve bootstrapping results, might used other calculations. sake of completeness here boot code:

#bootstrapping using boot package library(boot) #data<-read.csv(file.choose(),header=true) #read data selected file #x<-data[,c("wall","nrpk","lkwh","ylpr")] #only select relevant columns #x #check data  #sample data  #  wall nrpk lkwh ylpr #1    21    8    2    5 #2    57    9    0    1 #3    45    6    2    0 #4    17   10    3    0 #5    33    2    0    0 #6    41    4    0    0 #7    21    4    0    0 #8    32    7    6    0 #9     9    7    1    0 #10    9    4    0    0  i<-nrow(x) #count number of rows resampling  g<-ncol(x) #count number of columns step through bootstrapping boot.mean<-function(x,i){boot.mean<-mean(x[i])} #bootstrapping function mean  z<-boot(x, boot.mean,r=50000) #bootstrapping function, uses mean , number of reps boot.ci(z,type="perc") #derive 95% confidence intervals apply(x[1:g],2, boot.mean) #bootstrap columns  #output: #wall nrpk lkwh ylpr  #28.5  6.1  1.4  0.6  

i've gone through of resources can find , can't seem things working. output bootstrapped means associated confidence intervals each column. thanks!

note: apply(x[1:g],2, boot.mean) #bootstrap columns doesn't bootstrap. calculating mean each column.

for bootstrap mean , confidence interval, try this:

apply(x,2,function(y){     b<-boot(y,boot.mean,r=50000);     c(mean(b$t),boot.ci(b,type="perc", conf=0.95)$percent[4:5]) })