[R] bootstrap

[arun]

Hi,
You might need to check library(boot).  I have never used that before.  So, I can't comment much.  It is better to post on R-help list.  I had seen your postings on Nabble in the past.  Unfortunately those postings were not accepted in R-help.  You have to directly post at   r-help at r-project.org after registering at:
https://stat.ethz.ch/mailman/listinfo/r-help
 





________________________________
From: Angela Fel Padecio <solewolf301 at yahoo.com>
To: arun <smartpink111 at yahoo.com> 
Sent: Wednesday, May 29, 2013 9:05 AM
Subject: bootstrap



hi. i have these dataset: 

set.seed(12345) 
S=1000 
generate <- function(size) { 
x1 <- rnorm(size, mean=0, sd=1) 
x2 <- rnorm(size, mean=0, sd=1) 
x3 <- rnorm(size, mean=0, sd=1) 
x4 <- rnorm(size, mean=0, sd=1) 
x5 <- rnorm(size, mean=0, sd=1) 
x6 <- rnorm(size, mean=0, sd=1) 
x7 <- rnorm(size, mean=0, sd=1) 
x8 <- rnorm(size, mean=0, sd=1) 
x9 <- rnorm(size, mean=0, sd=1) 
x10 <- rnorm(size, mean=0, sd=1) 
e<-rnorm(size, mean=0, sd=1) 
t_trueps <- (1 + exp( -(b0 + b1*x1 + b2*x2 + b3*x3 + b4*x4 + b5*x5 + b6*x6 + b7*x7 
+ b2*x2*x2 + b4*x4*x4 + b7*x7*x7 + b1*0.5*x1*x3 + b2*0.7*x2*x4 +b3*0.5*x3*x5 
+ b4*0.7*x4*x6 + b5*0.5*x5*x7 + b1*0.5*x1*x6 + b2*0.7*x2*x3 + b3*0.5*x3*x4 
+ b4*0.5*x4*x5 + b5*0.5*x5*x6) ) )^-1 
prob.exposure <- runif(size) 
t <- ifelse(t_trueps > prob.exposure, 1, 0) 
y <- a0 + a1*x1 + a2*x2 + a3*x3 + a4*x4 +a5*x8 + a6*x9 + a7*x10 + g1*t + e 
sim <- as.data.frame(cbind(x1, x2, x3 ,x4, x5, x6, x7, x8, x9, x10, t, y)) 
return(sim) 
} 
b0 <- 0.05 
b1 <- 0.95 
b2 <- -0.25 
b3 <- 0.6 
b4 <- -0.4 
b5 <- -0.8 
b6 <- -0.5 
b7 <- 0.7 
a0 <- -3.85 
a1 <- 0.3 
a2 <- -0.36 
a3 <- -0.73 
a4 <- -0.2 
a5 <- 0.71 
a6 <- -0.19 
a7 <- 0.26 
g1 <- -0.4 

How can i have a bootstrap sample of 5 from size 10 with 1000 replications, i.e, 

data<-generate(10) 

where entire row is chosen. for example, if i have this result: 

> data<-generate(10) 
> data 
           x1          x2         x3          x4         x5         x6 
1   0.9374775 -2.26118020 -1.7502526 -0.04386488  0.6760577  0.5125265 
2  -1.3379878  0.54495810 -1.1884175 -0.25142873 -0.7389659 -2.7850113 
3  -0.5633375 -0.59191774 -1.4772120  0.74107022 -0.2862497  0.8067138 
4   0.3050390 -0.40174654  0.2980965  0.19234445  1.0762513  0.1604186 
5   0.6919353 -0.13762332 -0.5352159  0.69566392  1.3655018 -0.8463535 
6   0.2988476  1.15431908 -0.1172911  1.38397105  0.2631057  1.7943873 
7  -0.1424191 -0.06971174 -1.2759867 -1.25774074  1.2320712  1.7419884 
8   1.1835778 -0.06363542 -0.4772019 -0.46848004  1.0064428 -0.6327513 
9   0.1942304 -0.79500297 -1.1120049  0.60023523  0.2210129 -1.7187271 
10 -2.3568380  0.34227984 -1.0006803 -0.09190608  0.1187722 -0.5756797 
           x7                  x8                x9                 x10           t         y 
1   0.7249311  0.2420102  2.51106406  1.6699921 0 -2.019059 
2  -0.5209441  0.4935232 -0.31236000 -0.7717535 1 -2.286814 
3  -1.0086591  0.6120889 -0.19684965  0.3355901 0 -2.785737 
4  -0.4003396  0.9890145 -2.10427706  0.5364553 1 -2.782166 
5  -0.1662400 -0.1357740  0.80220396 -0.3509522 0 -2.424431 
6   2.1162941  1.4961478  0.02505993  0.8154658 1 -6.140725 
7   0.9965705  1.0531386  0.53474097 -0.1415918 0 -2.922637 
8  -0.1959067 -0.3507144  1.15341204  0.6018451 1 -2.602453 
9   1.0153402 -0.2612589 -0.70037063  0.4304613 1 -2.788079 
10  0.5378466  0.8504346  1.66384979 -1.2695204 0 -3.749164 

entire entries of row 1,3,5,7,9 for instance are chosen with 1000. your help is highly appreciated.