qrchk:
In musto101/wilcox_R: What the package does (short line)
Usage
1
Arguments
x
y
qval
q
nboot
com.pval
SEED
alpha
pr
xout
outfun
chk.table
MC
...
Examples
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##---- 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, qval = 0.5, q = NULL, nboot = 1000, com.pval = FALSE,
SEED = TRUE, alpha = 0.05, pr = TRUE, xout = FALSE, outfun = out,
chk.table = FALSE, MC = FALSE, ...)
{
if (!is.null(q))
qval = q
if (pr) {
if (!com.pval)
print("To get a p-value, set com.pval=T and use MC=T if a multicore processor is available")
print("Reject if test statistic is >= critical value")
}
x <- as.matrix(x)
p <- ncol(x)
pp1 <- p + 1
yx <- elimna(cbind(y, x))
y <- yx[, 1]
x <- yx[, 2:pp1]
store.it = F
x <- as.matrix(x)
p.val <- NULL
crit.val <- NULL
x <- as.matrix(x)
if (xout) {
flag <- outfun(x, ...)$keep
x <- x[flag, ]
y <- y[flag]
}
n <- length(y)
x = standm(x)
if (p <= 6) {
if (qval == 0.5) {
aval <- c(0.1, 0.05, 0.025, 0.01)
aokay <- duplicated(c(alpha, aval))
aokay <- sum(aokay)
if (aokay > 0) {
crit10 <- matrix(c(0.0254773, 0.008372, 0.00463254,
0.0023586, 0.000959315, 0.00042248, 0.00020069,
0.039728, 0.012163, 0.0069332, 0.0036521, 0.001571,
0.0006882, 0.0003621, 0.055215, 0.0173357,
0.009427, 0.004581, 0.0021378, 0.00093787,
0.00045287, 0.075832, 0.0228556, 0.0118571,
0.005924, 0.00252957, 0.0011593, 0.00056706,
0.103135, 0.0298896, 0.0151193, 0.0073057,
0.00305456, 0.001443, 0.000690435, 0.12977,
0.03891, 0.018989, 0.009053, 0.0036326, 0.001617,
0.000781457), ncol = 6, nrow = 7)
crit05 <- matrix(c(0.031494, 0.010257, 0.00626,
0.00303523, 0.0012993, 0.000562247, 0.00025972,
0.046296, 0.015066, 0.00885556, 0.0045485,
0.0110904, 0.00086946, 0.000452978, 0.063368,
0.0207096546, 0.010699, 0.005341, 0.0025426,
0.0011305, 0.000539873, 0.085461, 0.027256,
0.014067, 0.0071169, 0.002954, 0.0013671, 0.000660338,
0.11055, 0.03523, 0.017511, 0.0084263, 0.0036533,
0.0016338, 0.00081289, 0.13692, 0.043843, 0.0222425,
0.0102265, 0.004283, 0.0019, 0.000907241),
ncol = 6, nrow = 7)
crit025 <- matrix(c(0.0361936, 0.012518, 0.007296,
0.0036084, 0.00172436, 0.000725365, 0.000327776,
0.05315, 0.017593, 0.0102389, 0.0055043, 0.00227459,
0.0010062, 0.000523526, 0.07214, 0.023944,
0.013689, 0.0060686, 0.0028378, 0.00136379,
0.000635645, 0.093578, 0.0293223, 0.0156754,
0.0086059, 0.0035195, 0.001694, 0.00074467,
0.118414, 0.03885, 0.0201468, 0.0094298, 0.0040263,
0.00182437, 0.000916557, 0.14271, 0.047745,
0.0253974, 0.011385, 0.004725, 0.00207588,
0.0010191), ncol = 6, nrow = 7)
crit01 <- matrix(c(0.0414762, 0.0146553, 0.0098428,
0.0045274, 0.00219345, 0.00096244, 0.000443827,
0.058666, 0.020007, 0.01129658, 0.0063092,
0.002796, 0.0011364, 0.000628054, 0.079446,
0.0267958, 0.015428, 0.0071267, 0.0034163,
0.0015876, 0.000734865, 0.102736, 0.0357572,
0.017786, 0.0093682, 0.0042367, 0.0019717,
0.000868506, 0.125356, 0.041411, 0.0234916,
0.0106895, 0.0047028, 0.0020759, 0.00101052,
0.14837, 0.053246, 0.027759, 0.012723, 0.00528,
0.002437, 0.00116065), ncol = 6, nrow = 7)
if (alpha == 0.1)
critit <- crit10
if (alpha == 0.05)
critit <- crit05
if (alpha == 0.025)
critit <- crit025
if (alpha == 0.01)
critit <- crit01
nvec <- c(10, 20, 30, 50, 100, 200, 400)
nval <- duplicated(c(n, nvec))
nval <- nval[2:7]
if (sum(nval) > 0)
crit.val <- critit[nval, p]
if (is.null(crit.val)) {
if (n <= 400) {
loc <- rank(c(n, nvec))
xx <- c(1/nvec[loc[1] - 1]^1.5, 1/nvec[loc[1]]^1.5)
yy <- c(critit[loc[1] - 1, p], critit[loc[1],
p])
}
icoef <- lsfit(xx, yy)$coef
crit.val <- icoef[1] + icoef[2]/n^1.5
}
}
}
}
if (is.null(crit.val)) {
if (!com.pval) {
print("Critical values not available, will set com.pval=T")
print("and compute a p-value")
com.pval <- T
}
}
gdot <- cbind(rep(1, n), x)
gdot <- ortho(gdot)
x <- gdot[, 2:pp1]
x <- as.matrix(x)
temp <- rqfit(x, y, qval = qval, res = TRUE)
coef <- temp$coef
psi <- NA
psi <- ifelse(temp$residuals > 0, qval, qval - 1)
rnmat <- matrix(0, nrow = n, ncol = pp1)
ran.mat <- apply(x, 2, rank)
flagvec <- apply(ran.mat, 1, max)
for (j in 1:n) {
flag <- ifelse(flagvec <= flagvec[j], TRUE, FALSE)
flag <- as.numeric(flag)
rnmat[j, ] <- apply(flag * psi * gdot, 2, sum)
}
rnmat <- rnmat/sqrt(n)
temp <- matrix(0, pp1, pp1)
for (i in 1:n) temp <- temp + rnmat[i, ] %*% t(rnmat[i, ])
temp <- temp/n
test <- max(eigen(temp)$values)
if (com.pval) {
if (SEED)
set.seed(2)
if (MC)
library(parallel)
xy = list()
p1 = p + 1
for (i in 1:nboot) xy[[i]] = rmul(n, p = p1)
if (MC)
temp3 = mclapply(xy, qrchkv2.sub2, qval = qval, mc.preschedule = TRUE)
if (!MC)
temp3 = lapply(xy, qrchkv2.sub2, qval = qval)
rem = matl(temp3)
p.val = sum(test >= rem)
rem <- sort(rem)
p.val <- 1 - p.val/nboot
ic <- round((1 - alpha) * nboot)
crit.val <- rem[ic]
}
de = "Fail to reject"
if (test >= crit.val)
de = "Reject"
list(test.stat = test, crit.value = crit.val, p.value = p.val,
Decision = de)
}
musto101/wilcox_R documentation built on May 23, 2019, 10:52 a.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Usage
1 |
Arguments
x |
|
y |
|
qval |
|
q |
|
nboot |
|
com.pval |
|
SEED |
|
alpha |
|
pr |
|
xout |
|
outfun |
|
chk.table |
|
MC |
|
... |
Examples
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 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 | ##---- 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, qval = 0.5, q = NULL, nboot = 1000, com.pval = FALSE,
SEED = TRUE, alpha = 0.05, pr = TRUE, xout = FALSE, outfun = out,
chk.table = FALSE, MC = FALSE, ...)
{
if (!is.null(q))
qval = q
if (pr) {
if (!com.pval)
print("To get a p-value, set com.pval=T and use MC=T if a multicore processor is available")
print("Reject if test statistic is >= critical value")
}
x <- as.matrix(x)
p <- ncol(x)
pp1 <- p + 1
yx <- elimna(cbind(y, x))
y <- yx[, 1]
x <- yx[, 2:pp1]
store.it = F
x <- as.matrix(x)
p.val <- NULL
crit.val <- NULL
x <- as.matrix(x)
if (xout) {
flag <- outfun(x, ...)$keep
x <- x[flag, ]
y <- y[flag]
}
n <- length(y)
x = standm(x)
if (p <= 6) {
if (qval == 0.5) {
aval <- c(0.1, 0.05, 0.025, 0.01)
aokay <- duplicated(c(alpha, aval))
aokay <- sum(aokay)
if (aokay > 0) {
crit10 <- matrix(c(0.0254773, 0.008372, 0.00463254,
0.0023586, 0.000959315, 0.00042248, 0.00020069,
0.039728, 0.012163, 0.0069332, 0.0036521, 0.001571,
0.0006882, 0.0003621, 0.055215, 0.0173357,
0.009427, 0.004581, 0.0021378, 0.00093787,
0.00045287, 0.075832, 0.0228556, 0.0118571,
0.005924, 0.00252957, 0.0011593, 0.00056706,
0.103135, 0.0298896, 0.0151193, 0.0073057,
0.00305456, 0.001443, 0.000690435, 0.12977,
0.03891, 0.018989, 0.009053, 0.0036326, 0.001617,
0.000781457), ncol = 6, nrow = 7)
crit05 <- matrix(c(0.031494, 0.010257, 0.00626,
0.00303523, 0.0012993, 0.000562247, 0.00025972,
0.046296, 0.015066, 0.00885556, 0.0045485,
0.0110904, 0.00086946, 0.000452978, 0.063368,
0.0207096546, 0.010699, 0.005341, 0.0025426,
0.0011305, 0.000539873, 0.085461, 0.027256,
0.014067, 0.0071169, 0.002954, 0.0013671, 0.000660338,
0.11055, 0.03523, 0.017511, 0.0084263, 0.0036533,
0.0016338, 0.00081289, 0.13692, 0.043843, 0.0222425,
0.0102265, 0.004283, 0.0019, 0.000907241),
ncol = 6, nrow = 7)
crit025 <- matrix(c(0.0361936, 0.012518, 0.007296,
0.0036084, 0.00172436, 0.000725365, 0.000327776,
0.05315, 0.017593, 0.0102389, 0.0055043, 0.00227459,
0.0010062, 0.000523526, 0.07214, 0.023944,
0.013689, 0.0060686, 0.0028378, 0.00136379,
0.000635645, 0.093578, 0.0293223, 0.0156754,
0.0086059, 0.0035195, 0.001694, 0.00074467,
0.118414, 0.03885, 0.0201468, 0.0094298, 0.0040263,
0.00182437, 0.000916557, 0.14271, 0.047745,
0.0253974, 0.011385, 0.004725, 0.00207588,
0.0010191), ncol = 6, nrow = 7)
crit01 <- matrix(c(0.0414762, 0.0146553, 0.0098428,
0.0045274, 0.00219345, 0.00096244, 0.000443827,
0.058666, 0.020007, 0.01129658, 0.0063092,
0.002796, 0.0011364, 0.000628054, 0.079446,
0.0267958, 0.015428, 0.0071267, 0.0034163,
0.0015876, 0.000734865, 0.102736, 0.0357572,
0.017786, 0.0093682, 0.0042367, 0.0019717,
0.000868506, 0.125356, 0.041411, 0.0234916,
0.0106895, 0.0047028, 0.0020759, 0.00101052,
0.14837, 0.053246, 0.027759, 0.012723, 0.00528,
0.002437, 0.00116065), ncol = 6, nrow = 7)
if (alpha == 0.1)
critit <- crit10
if (alpha == 0.05)
critit <- crit05
if (alpha == 0.025)
critit <- crit025
if (alpha == 0.01)
critit <- crit01
nvec <- c(10, 20, 30, 50, 100, 200, 400)
nval <- duplicated(c(n, nvec))
nval <- nval[2:7]
if (sum(nval) > 0)
crit.val <- critit[nval, p]
if (is.null(crit.val)) {
if (n <= 400) {
loc <- rank(c(n, nvec))
xx <- c(1/nvec[loc[1] - 1]^1.5, 1/nvec[loc[1]]^1.5)
yy <- c(critit[loc[1] - 1, p], critit[loc[1],
p])
}
icoef <- lsfit(xx, yy)$coef
crit.val <- icoef[1] + icoef[2]/n^1.5
}
}
}
}
if (is.null(crit.val)) {
if (!com.pval) {
print("Critical values not available, will set com.pval=T")
print("and compute a p-value")
com.pval <- T
}
}
gdot <- cbind(rep(1, n), x)
gdot <- ortho(gdot)
x <- gdot[, 2:pp1]
x <- as.matrix(x)
temp <- rqfit(x, y, qval = qval, res = TRUE)
coef <- temp$coef
psi <- NA
psi <- ifelse(temp$residuals > 0, qval, qval - 1)
rnmat <- matrix(0, nrow = n, ncol = pp1)
ran.mat <- apply(x, 2, rank)
flagvec <- apply(ran.mat, 1, max)
for (j in 1:n) {
flag <- ifelse(flagvec <= flagvec[j], TRUE, FALSE)
flag <- as.numeric(flag)
rnmat[j, ] <- apply(flag * psi * gdot, 2, sum)
}
rnmat <- rnmat/sqrt(n)
temp <- matrix(0, pp1, pp1)
for (i in 1:n) temp <- temp + rnmat[i, ] %*% t(rnmat[i, ])
temp <- temp/n
test <- max(eigen(temp)$values)
if (com.pval) {
if (SEED)
set.seed(2)
if (MC)
library(parallel)
xy = list()
p1 = p + 1
for (i in 1:nboot) xy[[i]] = rmul(n, p = p1)
if (MC)
temp3 = mclapply(xy, qrchkv2.sub2, qval = qval, mc.preschedule = TRUE)
if (!MC)
temp3 = lapply(xy, qrchkv2.sub2, qval = qval)
rem = matl(temp3)
p.val = sum(test >= rem)
rem <- sort(rem)
p.val <- 1 - p.val/nboot
ic <- round((1 - alpha) * nboot)
crit.val <- rem[ic]
}
de = "Fail to reject"
if (test >= crit.val)
de = "Reject"
list(test.stat = test, crit.value = crit.val, p.value = p.val,
Decision = de)
}
|
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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