rollmeanRle <- function (x, k) { n <- length(x) cumsum(c(Rle(sum(window(x, 1, k))), window(x, k + 1, n) - window(x, 1, n - k))) / k }
rollvarRle <- function(x, k) { n <- length(x) means <- rollmeanRle(x, k) nextMean <- window(means, 2, n - k + 1) cumsum(c(Rle(sum((window(x, 1, k) - means[1])^2)), k * diff(means)^2 - (window(x, 1, n - k) - nextMean)^2 + (window(x, k + 1, n) - nextMean)^2)) / (k - 1) }
rollcovRle <- function(x, y, k) { n <- length(x) meanX <- rollmeanRle(x, k) meanY <- rollmeanRle(y, k) nextMeanX <- window(meanX, 2, n - k + 1) nextMeanY <- window(meanY, 2, n - k + 1) cumsum(c(Rle(sum((window(x, 1, k) - meanX[1]) * (window(y, 1, k) - meanY[1]))), k * diff(meanX) * diff(meanY) - (window(x, 1, n - k) - nextMeanX) * (window(y, 1, n - k) - nextMeanY) + (window(x, k + 1, n) - nextMeanX) * (window(y, k + 1, n) - nextMeanY))) / (k - 1) }
rollsdRle <- function(x, k) { sqrt(rollvarRle(x, k)) }
rollcorRle <- function(x, y, k) { rollcovRle(x, y, k) / (rollsdRle(x, k) * rollsdRle(y, k)) }
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