"bootstrap"<-
function(x, nboot, theta, ...)
{
        z<-list()
        data <- matrix(sample(x, size = length(x) * nboot, replace = T), nrow
                 = nboot)
        bd<-apply(data, 1, theta, ...)
        est<-theta(x,...)
        z$est<-est
        z$distn<-bd
        z$bias<-mean(bd)-est
        z$se<-sqrt(var(bd))
        z
}
"bootstrap2"<-
function(x, y, nboot, theta, ...)
{       z<-list()
        data.x <- matrix(sample(x, size = length(x) * nboot, replace = T), nrow
                 = nboot)
        data.y <- matrix(sample(y, size = length(y) * nboot, replace = T), nrow
                 = nboot)
        data <- cbind(data.x, data.y)
        bd<-apply(data, 1, theta, ...)
        est<-theta(c(x,y),...)
        z$est<-est
        z$distn<-bd
        z$bias<-mean(bd)-est
        z$se<-sqrt(var(bd))
        z
 
}



"theta1"<-
function(x, xdata)
{
	cor(xdata[x, 1], xdata[x, 2])
}



"theta4"<-
function(x, xdata)
{
	mc.lo <- loess(xdata[x, 2] ~ xdata[x, 1], span = 1/3)
	y <- predict.loess(mc.lo, 1:60)
	lines(1:60, y)
}



"theta5"<-
function(x, xdata)
{
	ls <- lsfit(xdata[x, 1], xdata[x, 2])
	abline(ls)
	ls$coef
}
"theta6"<-
function(x, xdata)
{
	y <- x + xdata[, 2]
	ls <- lsfit(xdata[, 1], y)
	abline(ls)
	ls$coef
}