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#' @describeIn bootSlope Bootstrap the slope of a simple linear regression line
#' @export
bootSlope.default <-
function(x, y, conf.level = 0.95, B = 10000, plot.hist = TRUE,
xlab = NULL, ylab = NULL, title = NULL,
plot.qq = FALSE, x.name=deparse(substitute(x)), y.name=deparse(substitute(y)),
seed = NULL, ...)
{
if (B%%1 != 0 || B < 2) stop("B must be a positive integer")
if(!is.null(seed)) set.seed(seed)
alpha <- 1 - conf.level
if (!is.numeric(x) || !is.numeric(y)) stop("Both variables must be numeric.")
comCases <- complete.cases(x, y)
nmiss <- length(x) - sum(comCases)
if (nmiss > 0)
cat("\n ", nmiss, "observation(s) removed due to missing values.\n")
x2 <- x[comCases]
y2 <- y[comCases]
observed <- round(cor(x2, y2) * sd(y2) / sd(x2), 4)
n <- length(x2)
#Boot
temp <- numeric(B)
for (i in 1:B)
{
index <- sample(1:n, n, replace = TRUE)
newx <- x2[index]
newy <- y2[index]
temp[i] <- cor(newx, newy) * sd(newy) / sd(newx)
} #end for
bootstrap.mean <- mean(temp)
# invisible(temp)
class(temp) <- "carlboot"
attr(temp, "observed") <- observed
attr(temp, "statistic") <- "slope"
attr(temp, "groups") <- NULL
attr(temp, "x.name") <- x.name
attr(temp, "y.name") <- y.name
attr(temp, "level") <- conf.level
attr(temp, "xlab") <- xlab
attr(temp, "ylab") <- ylab
attr(temp, "title") <- title
attr(temp, "plot.hist") <- plot.hist
attr(temp, "plot.qq") <- plot.qq
temp
}
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