The R Project SVN R-packages

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grav.z <- (grav.boot$t[, 1]-grav.boot$t0[1])/sqrt(grav.boot$t[, 2])
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grav.z <- (grav.boot$t[, 1]-grav.boot$t0[1])/sqrt(grav.boot$t[, 2])
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plot(grav.boot, t = grav.z, t0 = 0)
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plot(grav.boot, t = grav.z, t0 = 0)
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# In this example we look at the one of the partial correlations for the
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# In this example we look at the one of the partial correlations for the
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# head dimensions in the dataset frets.
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# head dimensions in the dataset frets.
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pcorr <- function(x) {
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#  Function to find the correlations and partial correlations between
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#  the four measurements.
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     v <- cor(x)
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     v.d <- diag(var(x))
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     iv <- solve(v)
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     iv.d <- sqrt(diag(iv))
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     iv <- - diag(1/iv.d) \%*\% iv \%*\% diag(1/iv.d)
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     q <- NULL
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     n <- nrow(v)
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     for (i in 1:(n-1))
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          q <- rbind( q, c(v[i, 1:i], iv[i, (i+1):n]) )
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     q <- rbind( q, v[n, ] )
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     diag(q) <- round(diag(q))
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     q
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}
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frets.fun <- function(data, i) {
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frets.fun <- function(data, i) {
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    pcorr <- function(x) {
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    #  Function to find the correlations and partial correlations between
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    #  the four measurements.
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         v <- cor(x)
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         v.d <- diag(var(x))
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         iv <- solve(v)
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         iv.d <- sqrt(diag(iv))
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         iv <- - diag(1/iv.d) \%*\% iv \%*\% diag(1/iv.d)
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         q <- NULL
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         n <- nrow(v)
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         for (i in 1:(n-1))
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              q <- rbind( q, c(v[i, 1:i], iv[i,(i+1):n]) )
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         q <- rbind( q, v[n, ] )
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         diag(q) <- round(diag(q))
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         q
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    }
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     d <- data[i, ]
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    d <- data[i, ]
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     v <- pcorr(d)
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    v <- pcorr(d)
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     c(v[1, ], v[2, ], v[3, ], v[4, ])
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    c(v[1,], v[2,], v[3,], v[4,])
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}
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}
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frets.boot <- boot(log(as.matrix(frets)),  frets.fun,  R = 999)
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frets.boot <- boot(log(as.matrix(frets)),  frets.fun,  R = 999)
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plot(frets.boot, index = 7, jack = TRUE, stinf = FALSE, useJ = FALSE)
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plot(frets.boot, index = 7, jack = TRUE, stinf = FALSE, useJ = FALSE)
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}
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}
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\keyword{hplot}
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\keyword{hplot}