1 |
x |
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y |
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sop |
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pyhat |
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eout |
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xout |
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outfun |
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plotit |
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xlab |
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ylab |
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zlab |
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theta |
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phi |
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expand |
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scale |
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ticktype |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 | ##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (x, y, sop = TRUE, pyhat = FALSE, eout = FALSE, xout = FALSE,
outfun = out, plotit = TRUE, xlab = "X", ylab = "", zlab = "",
theta = 50, phi = 25, expand = 0.5, scale = TRUE, ticktype = "simple")
{
library(akima)
library(mgcv)
x <- as.matrix(x)
np <- ncol(x)
np1 <- np + 1
if (ncol(x) > 4)
stop("x should have at most four columns of data")
m <- elimna(cbind(x, y))
x <- m[, 1:np]
x <- as.matrix(x)
y <- m[, np1]
if (xout && eout)
stop("Can't have xout=eout=T")
if (eout) {
flag <- outfun(m)$keep
m <- m[flag, ]
}
if (xout) {
flag <- outfun(x, plotit = FALSE)$keep
m <- m[flag, ]
}
x <- m[, 1:np]
x <- as.matrix(x)
y <- m[, np1]
if (!sop) {
if (ncol(x) == 1)
fitr <- fitted(gam(y ~ x[, 1]))
if (ncol(x) == 2)
fitr <- fitted(gam(y ~ x[, 1] + x[, 2]))
if (ncol(x) == 3)
fitr <- fitted(gam(y ~ x[, 1] + x[, 2] + x[, 3]))
if (ncol(x) == 4)
fitr <- fitted(gam(y ~ x[, 1] + x[, 2] + x[, 3] +
x[, 4]))
}
if (sop) {
if (ncol(x) == 1)
fitr <- fitted(gam(y ~ s(x[, 1])))
if (ncol(x) == 2)
fitr <- fitted(gam(y ~ s(x[, 1]) + s(x[, 2])))
if (ncol(x) == 3)
fitr <- fitted(gam(y ~ s(x[, 1]) + s(x[, 2]) + s(x[,
3])))
if (ncol(x) == 4)
fitr <- fitted(gam(y ~ s(x[, 1]) + s(x[, 2]) + s(x[,
3]) + s(x[, 4])))
}
last <- fitr
if (plotit) {
if (ncol(x) == 1) {
plot(x, fitr, xlab = xlab, ylab = ylab)
}
if (ncol(x) == 2) {
iout <- c(1:length(fitr))
nm1 <- length(fitr) - 1
for (i in 1:nm1) {
ip1 <- i + 1
for (k in ip1:length(fitr)) if (sum(x[i, ] ==
x[k, ]) == 2)
iout[k] <- 0
}
fitr <- fitr[iout >= 1]
mkeep <- x[iout >= 1, ]
fitr <- interp(mkeep[, 1], mkeep[, 2], fitr)
persp(fitr, theta = theta, phi = phi, expand = expand,
xlab = xlab, ylab = ylab, zlab = zlab, scale = scale,
ticktype = ticktype)
}
}
if (!pyhat)
last <- "Done"
last
}
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