Nothing
dFriedman <-
function (x, r, N, log = FALSE)
{
M <- max(length(x), length(r), length(N))
x <- rep(x, length.out = M)
r <- rep(r, length.out = M)
N <- rep(N, length.out = M)
rho <- rep(FALSE, length.out = M)
value <- .C(`dFriedmanR`, as.double(x), as.integer(r), as.integer(N),
as.integer(M), as.integer(rho), val = double(M),PACKAGE="SuppDists")$val
if (log == TRUE)
value <- log(value)
value
}
dghyper <-
function (x, a, k, N, log = FALSE)
{
M <- max(length(x), length(a), length(k), length(N))
x <- rep(x, length.out = M)
a <- rep(a, length.out = M)
k <- rep(k, length.out = M)
N <- rep(N, length.out = M)
value <- .C(`dghyperR`, as.integer(x), as.double(a), as.double(k),
as.double(N), as.integer(M), val = double(M),PACKAGE="SuppDists")$val
if (log == TRUE)
value <- log(value)
value
}
dinvGauss <-
function (x, nu, lambda, log = FALSE)
{
N <- max(length(x), length(nu), length(lambda))
x <- rep(x, length.out = N)
nu <- rep(nu, length.out = N)
lambda <- rep(lambda, length.out = N)
value <- .C(`dinvGaussR`, as.double(x), as.double(nu), as.double(lambda),
as.integer(N), lambda = double(N),PACKAGE="SuppDists")$lambda
if (log == TRUE)
value <- log(value)
value
}
dJohnson <-
function (x, parms, log = FALSE)
{
tfun <- function(x) if (x == "SN")
1
else if (x == "SL")
2
else if (x == "SU")
3
else 4
vecFromList <- function(item, aList) {
if (!is.list(aList[[1]]))
return(aList[[item]])
else {
tVec <- vector(length = 0)
for (i in 1:length(aList)) {
tVec <- append(tVec, (aList[[i]])[[item]])
}
}
tVec
}
gamma <- vecFromList(1, parms)
delta <- vecFromList(2, parms)
xi <- vecFromList(3, parms)
lambda <- vecFromList(4, parms)
type <- vecFromList(5, parms)
type <- sapply(type, tfun)
N <- max(length(gamma), length(x))
x <- rep(x, length.out = N)
gamma <- rep(gamma, length.out = N)
delta <- rep(delta, length.out = N)
xi <- rep(xi, length.out = N)
lambda <- rep(lambda, length.out = N)
type <- rep(type, length.out = N)
value <- .C(`dJohnsonR`, as.double(x), as.double(gamma),
as.double(delta), as.double(xi), as.double(lambda), as.integer(type),
as.integer(N), val = double(N),PACKAGE="SuppDists")$val
if (log == TRUE)
value <- log(value)
value
}
dKendall <-
function (x, N, log = FALSE)
{
M <- max(length(x), length(N))
x <- rep(x, length.out = M)
N <- rep(N, length.out = M)
value <- .C(`dKendallR`, as.integer(N), as.double(x), as.integer(M),
val = double(M),PACKAGE="SuppDists")$val
if (log == TRUE)
value <- log(value)
value
}
dKruskalWallis <-
function (x, c, N, U, log = FALSE)
{
M <- max(length(x), length(c), length(N), length(U))
x <- rep(x, length.out = M)
c <- rep(c, length.out = M)
n <- rep(N, length.out = M)
U <- rep(U, length.out = M)
Ns <- rep(FALSE, length.out = M)
value <- .C(`dKruskalWallisR`, as.double(x), as.integer(c),
as.integer(n), as.double(U), as.integer(Ns), as.integer(M),
val = double(M),PACKAGE="SuppDists")$val
if (log == TRUE)
value <- log(value)
value
}
dmaxFratio <-
function (x, df, k, log = FALSE)
{
if (log == TRUE)
p <- exp(p)
N <- max(length(x), length(df), length(k))
x <- rep(x, length.out = N)
df <- rep(df, length.out = N)
k <- rep(k, length.out = N)
.C(`dmaxFratioR`, as.double(x), as.integer(df), as.integer(k),
as.integer(N), val = double(N),PACKAGE="SuppDists")$val
}
dNormScore <-
function (x, c, N, U, log = FALSE)
{
M <- max(length(x), length(c), length(N), length(U))
x <- rep(x, length.out = M)
c <- rep(c, length.out = M)
n <- rep(N, length.out = M)
U <- rep(U, length.out = M)
Ns <- rep(TRUE, length.out = M)
value <- .C(`dKruskalWallisR`, as.double(x), as.integer(c),
as.integer(n), as.double(U), as.integer(Ns), as.integer(M),
val = double(M),PACKAGE="SuppDists")$val
if (log == TRUE)
value <- log(value)
value
}
dPearson <-
function (x, N, rho = 0, log = FALSE)
{
M <- max(length(x), length(rho), length(N))
x <- rep(x, length.out = M)
rho <- rep(rho, length.out = M)
N <- rep(N, length.out = M)
value <- .C(`dcorrR`, as.double(x), as.double(rho), as.integer(N),
as.integer(M), val = double(M),PACKAGE="SuppDists")$val
if (log == TRUE)
value <- log(value)
value
}
dSpearman <-
function (x, r, log = FALSE)
{
M <- max(length(x), length(r))
x <- rep(x, length.out = M)
r <- rep(r, length.out = M)
N <- rep(2, length.out = M)
rho <- rep(TRUE, length.out = M)
value <- .C(`dFriedmanR`, as.double(x), as.integer(r), as.integer(N),
as.integer(M), as.integer(rho), val = double(M),PACKAGE="SuppDists")$val
if (log == TRUE)
value <- log(value)
value
}
JohnsonFit <-
function (t, moment = "quant")
{
firstChar=substring(moment,1,1)
if (firstChar=="f") {
mom <- moments(t)
mu <- mom[[1]]
sigma <- mom[[2]]
skew <- mom[[3]]
kurt <- mom[[4]]
value <- .C(`JohnsonMomentFitR`, as.double(mu), as.double(sigma),
as.double(skew), as.double(kurt), gamma = double(1),
delta = double(1), xi = double(1), lambda = double(1),
type = integer(1),PACKAGE="SuppDists")
}
else if (firstChar=="u") {
mu<-t[1]
sigma<-sqrt(t[2])
skew<-t[3]/sigma^3
kurt<-(t[4]/t[2]^2)-3
value <- .C(`JohnsonMomentFitR`, as.double(mu), as.double(sigma),
as.double(skew), as.double(kurt), gamma = double(1),
delta = double(1), xi = double(1), lambda = double(1),
type = integer(1),PACKAGE="SuppDists")
}
else if (firstChar=="q") {
input <- quantile(t, probs = c(0.05, 0.206, 0.5, 0.794,
0.95), names = FALSE)
x5 <- input[[1]]
x20.6 <- input[[2]]
x50 <- input[[3]]
x79.4 <- input[[4]]
x95 <- input[[5]]
value <- .C(`JohnsonFitR`, as.double(x95), as.double(x79.4),
as.double(x50), as.double(x20.6), as.double(x5),
gamma = double(1), delta = double(1), xi = double(1),
lambda = double(1), type = integer(1),PACKAGE="SuppDists")
}
else return(NA)
types <- c("SN", "SL", "SU", "SB")
list(gamma = value$gamma, delta = value$delta, xi = value$xi,
lambda = value$lambda, type = types[value$type])
}
makeStatList <-
function (head, mn, med, var, mod, third, fourth, dig)
{
sd <- sqrt(var)
skew <- sign(third) * abs(third)/sd^3
kurt <- -3 + fourth/var^2
pskew <- (mn - mod)/sd
if (dig > 0) {
mn <- round(mn, digits = dig)
med <- round(med, digits = dig)
mod <- round(mod, digits = dig)
var <- round(var, digits = dig)
sd <- round(sd, digits = dig)
third <- round(third, digits = dig)
fourth <- round(fourth, digits = dig)
pskew <- round(pskew, digits = dig)
skew <- round(skew, digits = dig)
kurt <- round(kurt, digits = dig)
}
theList <- list(Mean = mn, Median = med, Mode = mod, Variance = var,
SD = sd, ThirdCentralMoment = third, FourthCentralMoment = fourth,
PearsonsSkewness...mean.minus.mode.div.SD = pskew, Skewness...sqrtB1 = skew,
Kurtosis...B2.minus.3 = kurt)
c(head, theList)
}
moments <-
function (x)
{
N <- length(x)
v <- ((N - 1)/N) * var(x)
sigma <- sqrt(v)
m3 <- (sum((x - mean(x))^3))/N
skew <- m3/sigma^3
m4 <- (sum((x - mean(x))^4))/N
kurt <- (m4/v^2) - 3
c(mean = mean(x), sigma = sigma, skew = skew, kurt = kurt)
}
normOrder <-
function (N)
{
N <- if (length(N) > 1)
length(N)
else N
M <- N%/%2
value <- .C(`normOrdR`, val = double(M), as.integer(N), as.integer(M),PACKAGE="SuppDists")$val
if (0 == N%%2)
c(-value, rev(value))
else c(-value, 0, rev(value))
}
pFriedman <-
function (q, r, N, lower.tail = TRUE, log.p = FALSE)
{
M <- max(length(q), length(r), length(N))
q <- rep(q, length.out = M)
r <- rep(r, length.out = M)
N <- rep(N, length.out = M)
rho <- rep(FALSE, length.out = M)
if (lower.tail == TRUE) {
value <- .C(`pFriedmanR`, as.double(q), as.integer(r),
as.integer(N), as.integer(M), as.integer(rho), val = double(M),PACKAGE="SuppDists")$val
}
else {
value <- .C(`uFriedmanR`, as.double(q), as.integer(r),
as.integer(N), as.integer(M), as.integer(rho), val = double(M),PACKAGE="SuppDists")$val
}
if (log.p == TRUE)
value <- log(value)
value
}
pghyper <-
function (q, a, k, N, lower.tail = TRUE, log.p = FALSE)
{
M <- max(length(q), length(a), length(k), length(N))
q <- rep(q, length.out = M)
a <- rep(a, length.out = M)
k <- rep(k, length.out = M)
N <- rep(N, length.out = M)
if (lower.tail == TRUE) {
value <- .C(`pghyperR`, as.integer(q), as.double(a),
as.double(k), as.double(N), as.integer(M), val = double(M),PACKAGE="SuppDists")$val
}
else {
value <- .C(`ughyperR`, as.integer(q), as.double(a),
as.double(k), as.double(N), as.integer(M), val = double(M),PACKAGE="SuppDists")$val
}
if (log.p == TRUE)
value <- log(value)
value
}
pinvGauss <-
function (q, nu, lambda, lower.tail = TRUE, log.p = FALSE)
{
N <- max(length(q), length(nu), length(lambda))
q <- rep(q, length.out = N)
nu <- rep(nu, length.out = N)
lambda <- rep(lambda, length.out = N)
if (lower.tail == TRUE) {
value <- .C(`pinvGaussR`, as.double(q), as.double(nu),
as.double(lambda), as.integer(N), val = double(N),PACKAGE="SuppDists")$val
}
else {
value <- .C(`uinvGaussR`, as.double(q), as.double(nu),
as.double(lambda), as.integer(N), val = double(N),PACKAGE="SuppDists")$val
}
if (log.p == TRUE)
value <- log(value)
value
}
pJohnson <-
function (q, parms, lower.tail = TRUE, log.p = FALSE)
{
tfun <- function(x) if (x == "SN")
1
else if (x == "SL")
2
else if (x == "SU")
3
else 4
vecFromList <- function(item, aList) {
if (!is.list(aList[[1]]))
return(aList[[item]])
else {
tVec <- vector(length = 0)
for (i in 1:length(aList)) {
tVec <- append(tVec, (aList[[i]])[[item]])
}
}
tVec
}
gamma <- vecFromList(1, parms)
delta <- vecFromList(2, parms)
xi <- vecFromList(3, parms)
lambda <- vecFromList(4, parms)
type <- vecFromList(5, parms)
type <- sapply(type, tfun)
N <- max(length(gamma), length(q))
q <- rep(q, length.out = N)
gamma <- rep(gamma, length.out = N)
delta <- rep(delta, length.out = N)
xi <- rep(xi, length.out = N)
lambda <- rep(lambda, length.out = N)
type <- rep(type, length.out = N)
if (lower.tail == TRUE) {
value <- .C(`pJohnsonR`, as.double(q), as.double(gamma),
as.double(delta), as.double(xi), as.double(lambda),
as.integer(type), as.integer(N), val = double(N),PACKAGE="SuppDists")$val
}
else {
value <- .C(`uJohnsonR`, as.double(q), as.double(gamma),
as.double(delta), as.double(xi), as.double(lambda),
as.integer(type), as.integer(N), val = double(N),PACKAGE="SuppDists")$val
}
if (log.p == TRUE)
value <- log(value)
value
}
pKendall <-
function (q, N, lower.tail = TRUE, log.p = FALSE)
{
M <- max(length(q), length(N))
q <- rep(q, length.out = M)
N <- rep(N, length.out = M)
if (lower.tail == TRUE) {
value <- .C(`pKendallR`, as.integer(N), as.double(q),
as.integer(M), val = double(M),PACKAGE="SuppDists")$val
}
else {
value <- .C(`uKendallR`, as.integer(N), as.double(q),
as.integer(M), val = double(M),PACKAGE="SuppDists")$val
}
if (log.p == TRUE)
value <- log(value)
value
}
pKruskalWallis <-
function (q, c, N, U, lower.tail = TRUE, log.p = FALSE)
{
M <- max(length(q), length(c), length(N), length(U))
q <- rep(q, length.out = M)
c <- rep(c, length.out = M)
n <- rep(N, length.out = M)
U <- rep(U, length.out = M)
Ns <- rep(FALSE, length.out = M)
if (lower.tail == TRUE) {
value <- .C(`pKruskalWallisR`, as.double(q), as.integer(c),
as.integer(n), as.double(U), as.integer(Ns), as.integer(M),
val = double(M),PACKAGE="SuppDists")$val
}
else {
value <- .C(`uKruskalWallisR`, as.double(q), as.integer(c),
as.integer(n), as.double(U), as.integer(Ns), as.integer(M),
val = double(M),PACKAGE="SuppDists")$val
}
if (log.p == TRUE)
value <- log(value)
value
}
pmaxFratio <-
function (q, df, k, lower.tail = TRUE, log.p = FALSE)
{
N <- max(length(q), length(df), length(k))
q <- rep(q, length.out = N)
df <- rep(df, length.out = N)
k <- rep(k, length.out = N)
if (lower.tail == TRUE) {
value <- .C(`pmaxFratioR`, as.double(q), as.integer(df),
as.integer(k), as.integer(N), val = double(N),PACKAGE="SuppDists")$val
}
else {
value <- .C(`umaxFratioR`, as.double(q), as.integer(df),
as.integer(k), as.integer(N), val = double(N),PACKAGE="SuppDists")$val
}
if (log.p == TRUE)
value <- log(value)
value
}
pNormScore <-
function (q, c, N, U, lower.tail = TRUE, log.p = FALSE)
{
M <- max(length(q), length(c), length(N), length(U))
q <- rep(q, length.out = M)
c <- rep(c, length.out = M)
n <- rep(N, length.out = M)
U <- rep(U, length.out = M)
Ns <- rep(TRUE, length.out = M)
if (lower.tail == TRUE) {
value <- .C(`pKruskalWallisR`, as.double(q), as.integer(c),
as.integer(n), as.double(U), as.integer(Ns), as.integer(M),
val = double(M),PACKAGE="SuppDists")$val
}
else {
value <- .C(`uKruskalWallisR`, as.double(q), as.integer(c),
as.integer(n), as.double(U), as.integer(Ns), as.integer(M),
val = double(M),PACKAGE="SuppDists")$val
}
if (log.p == TRUE)
value <- log(value)
value
}
pPearson <-
function (q, N, rho = 0, lower.tail = TRUE, log.p = FALSE)
{
M <- max(length(q), length(rho), length(N))
q <- rep(q, length.out = M)
rho <- rep(rho, length.out = M)
N <- rep(N, length.out = M)
if (lower.tail == TRUE) {
value <- .C(`pcorrR`, as.double(q), as.double(rho), as.integer(N),
as.integer(M), val = double(M),PACKAGE="SuppDists")$val
}
else {
value <- .C(`ucorrR`, as.double(q), as.double(rho), as.integer(N),
as.integer(M), val = double(M),PACKAGE="SuppDists")$val
}
if (log.p == TRUE)
value <- log(value)
value
}
pSpearman <-
function (q, r, lower.tail = TRUE, log.p = FALSE)
{
M <- max(length(q), length(r))
q <- rep(q, length.out = M)
r <- rep(r, length.out = M)
N <- rep(2, length.out = M)
rho <- rep(TRUE, length.out = M)
if (lower.tail == TRUE) {
value <- .C(`pFriedmanR`, as.double(q), as.integer(r),
as.integer(N), as.integer(M), as.integer(rho), val = double(M),PACKAGE="SuppDists")$val
}
else {
value <- .C(`uFriedmanR`, as.double(q), as.integer(r),
as.integer(N), as.integer(M), as.integer(rho), val = double(M),PACKAGE="SuppDists")$val
}
if (log.p == TRUE)
value <- log(value)
value
}
qFriedman <-
function (p, r, N, lower.tail = TRUE, log.p = FALSE)
{
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
M <- max(length(p), length(r), length(N))
p <- rep(p, length.out = M)
r <- rep(r, length.out = M)
N <- rep(N, length.out = M)
rho <- rep(FALSE, length.out = M)
.C(`qFriedmanR`, as.double(p), as.integer(r), as.integer(N),
as.integer(M), as.integer(rho), val = double(M),PACKAGE="SuppDists")$val
}
qghyper <-
function (p, a, k, N, lower.tail = TRUE, log.p = FALSE)
{
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
M <- max(length(p), length(a), length(k), length(N))
p <- rep(p, length.out = M)
a <- rep(a, length.out = M)
k <- rep(k, length.out = M)
N <- rep(N, length.out = M)
value <- .C(`qghyperR`, as.double(p), as.double(a), as.double(k),
as.double(N), as.integer(M), val = double(M),PACKAGE="SuppDists")$val
value
}
qinvGauss <-
function (p, nu, lambda, lower.tail = TRUE, log.p = FALSE)
{
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
N <- max(length(p), length(nu), length(lambda))
p <- rep(p, length.out = N)
nu <- rep(nu, length.out = N)
lambda <- rep(lambda, length.out = N)
.C(`qinvGaussR`, as.double(p), as.double(nu), as.double(lambda),
as.integer(N), value = double(N),PACKAGE="SuppDists")$value
}
qJohnson <-
function (p, parms, lower.tail = TRUE, log.p = FALSE)
{
tfun <- function(x) if (x == "SN")
1
else if (x == "SL")
2
else if (x == "SU")
3
else 4
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
vecFromList <- function(item, aList) {
if (!is.list(aList[[1]]))
return(aList[[item]])
else {
tVec <- vector(length = 0)
for (i in 1:length(aList)) {
tVec <- append(tVec, (aList[[i]])[[item]])
}
}
tVec
}
gamma <- vecFromList(1, parms)
delta <- vecFromList(2, parms)
xi <- vecFromList(3, parms)
lambda <- vecFromList(4, parms)
type <- vecFromList(5, parms)
type <- sapply(type, tfun)
N <- max(length(gamma), length(p))
p <- rep(p, length.out = N)
gamma <- rep(gamma, length.out = N)
delta <- rep(delta, length.out = N)
xi <- rep(xi, length.out = N)
lambda <- rep(lambda, length.out = N)
type <- rep(type, length.out = N)
.C(`qJohnsonR`, as.double(p), as.double(gamma), as.double(delta),
as.double(xi), as.double(lambda), as.integer(type), as.integer(N),
val = double(N),PACKAGE="SuppDists")$val
}
qKendall <-
function (p, N, lower.tail = TRUE, log.p = FALSE)
{
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
M <- max(length(p), length(N))
p <- rep(p, length.out = M)
N <- rep(N, length.out = M)
.C(`qKendallR`, as.integer(N), as.double(p), as.integer(M),
val = double(M),PACKAGE="SuppDists")$val
}
qKruskalWallis <-
function (p, c, N, U, lower.tail = TRUE, log.p = FALSE)
{
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
M <- max(length(p), length(c), length(N), length(U))
p <- rep(p, length.out = M)
c <- rep(c, length.out = M)
N <- rep(N, length.out = M)
U <- rep(U, length.out = M)
Ns <- rep(FALSE, length.out = M)
.C(`qKruskalWallisR`, as.double(p), as.integer(c), as.integer(N),
as.double(U), as.integer(Ns), as.integer(M), val = double(M),PACKAGE="SuppDists")$val
}
qmaxFratio <-
function (p, df, k, lower.tail = TRUE, log.p = FALSE)
{
if (lower.tail == FALSE)
p <- 1 - p
if (log.p == TRUE)
p <- exp(p)
N <- max(length(p), length(df), length(k))
p <- rep(p, length.out = N)
df <- rep(df, length.out = N)
k <- rep(k, length.out = N)
.C(`qmaxFratioR`, as.double(p), as.integer(df), as.integer(k),
as.integer(N), val = double(N),PACKAGE="SuppDists")$val
}
qNormScore <-
function (p, c, N, U, lower.tail = TRUE, log.p = FALSE)
{
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
M <- max(length(p), length(c), length(N), length(U))
p <- rep(p, length.out = M)
c <- rep(c, length.out = M)
N <- rep(N, length.out = M)
U <- rep(U, length.out = M)
Ns <- rep(TRUE, length.out = M)
.C(`qKruskalWallisR`, as.double(p), as.integer(c), as.integer(N),
as.double(U), as.integer(Ns), as.integer(M), val = double(M),PACKAGE="SuppDists")$val
}
qPearson <-
function (p, N, rho = 0, lower.tail = TRUE, log.p = FALSE)
{
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
M <- max(length(p), length(rho), length(N))
p <- rep(p, length.out = M)
rho <- rep(rho, length.out = M)
N <- rep(N, length.out = M)
.C(`qcorrR`, as.double(p), as.double(rho), as.integer(N),
as.integer(M), val = double(M),PACKAGE="SuppDists")$val
}
qSpearman <-
function (p, r, lower.tail = TRUE, log.p = FALSE)
{
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
M <- max(length(p), length(r))
p <- rep(p, length.out = M)
r <- rep(r, length.out = M)
N <- rep(2, length.out = M)
rho <- rep(TRUE, length.out = M)
.C(`qFriedmanR`, as.double(p), as.integer(r), as.integer(N),
as.integer(M), as.integer(rho), val = double(M),PACKAGE="SuppDists")$val
}
rFriedman <-
function (n, r, N)
{
n <- if (length(n) > 1)
length(n)
else n
M <- max(length(r), length(N))
r <- rep(r, length.out = M)
N <- rep(N, length.out = M)
rho <- rep(FALSE, length.out = M)
.C(`rFriedmanR`, as.integer(r), as.integer(N), as.integer(rho),
as.integer(n), as.integer(M), value = double(n),PACKAGE="SuppDists")$value
}
rghyper <-
function (n, a, k, N)
{
n <- if (length(n) > 1)
length(n)
else n
K <- max(length(a), length(k), length(N))
a <- rep(a, length.out = K)
k <- rep(k, length.out = K)
N <- rep(N, length.out = K)
.C(`rghyperR`, as.double(a), as.double(k), as.double(N),
as.integer(n), as.integer(K), value = double(n),PACKAGE="SuppDists")$value
}
rinvGauss <-
function (n, nu, lambda)
{
n <- if (length(n) > 1)
length(n)
else n
N <- max(length(nu), length(lambda))
nu <- rep(nu, length.out = N)
lambda <- rep(lambda, length.out = N)
.C(`rinvGaussR`, as.double(nu), as.double(lambda), as.integer(n),
as.integer(N), value = double(n),PACKAGE="SuppDists")$value
}
rJohnson <-
function (n, parms)
{
tfun <- function(x) if (x == "SN")
1
else if (x == "SL")
2
else if (x == "SU")
3
else 4
vecFromList <- function(item, aList) {
if (!is.list(aList[[1]]))
return(aList[[item]])
else {
tVec <- vector(length = 0)
for (i in 1:length(aList)) {
tVec <- append(tVec, (aList[[i]])[[item]])
}
}
tVec
}
n <- if (length(n) > 1)
length(n)
else n
gamma <- vecFromList(1, parms)
delta <- vecFromList(2, parms)
xi <- vecFromList(3, parms)
lambda <- vecFromList(4, parms)
type <- vecFromList(5, parms)
type <- sapply(type, tfun)
M <- length(gamma)
.C(`rJohnsonR`, as.double(gamma), as.double(delta), as.double(xi),
as.double(lambda), as.integer(type), as.integer(n), as.integer(M),
val = double(n),PACKAGE="SuppDists")$val
}
rKendall <-
function (n, N)
{
n <- if (length(n) > 1)
length(n)
else n
M <- length(N)
.C(`rKendallR`, as.integer(N), as.integer(n), as.integer(M),
val = double(n),PACKAGE="SuppDists")$val
}
rKruskalWallis <-
function (n, c, N, U)
{
n <- if (length(n) > 1)
length(n)
else n
M <- max(length(c), length(N), length(U))
c <- rep(c, length.out = M)
N <- rep(N, length.out = M)
U <- rep(U, length.out = M)
Ns <- rep(FALSE, length.out = M)
.C(`rKruskalWallisR`, randArray = double(n), as.integer(n),
as.integer(M), as.integer(c), as.integer(N), as.double(U),
as.integer(Ns),PACKAGE="SuppDists" )$randArray
}
rmaxFratio <-
function (n, df, k)
{
n <- if (length(n) > 1)
length(n)
else n
M <- max(length(df), length(k))
df <- rep(df, length.out = M)
k <- rep(k, length.out = M)
.C(`rmaxFratioR`, as.integer(df), as.integer(k), as.integer(n),
as.integer(M), value = double(n),PACKAGE="SuppDists")$value
}
## .Defunct
## no alternative
#rMWC1019 <-
#function (n, new.start = FALSE, seed = 556677)
#{
# n <- if (length(n) == 1)
# n
# else length(n)
# .C(`MWC1019R`, val = double(n), as.integer(n), as.integer(new.start),
# as.integer(seed),PACKAGE="SuppDists")$val
#}
rNormScore <-
function (n, c, N, U)
{
n <- if (length(n) > 1)
length(n)
else n
M <- max(length(c), length(N), length(U))
c <- rep(c, length.out = M)
N <- rep(N, length.out = M)
U <- rep(U, length.out = M)
Ns <- rep(TRUE, length.out = M)
.C(`rKruskalWallisR`, randArray = double(n), as.integer(n),
as.integer(M), as.integer(c), as.integer(N), as.double(U),
as.integer(Ns),PACKAGE="SuppDists" )$randArray
}
rPearson <-
function (n, N, rho = 0)
{
n <- if (length(n) > 1)
length(n)
else n
M <- max(length(rho), length(N))
rho <- rep(rho, length.out = M)
N <- rep(N, length.out = M)
.C(`rcorrR`, as.double(rho), as.integer(N), as.integer(n),
as.integer(M), val = double(n),PACKAGE="SuppDists")$val
}
rSpearman <-
function (n, r)
{
n <- if (length(n) > 1)
length(n)
else n
M <- length(r)
r <- rep(r, length.out = M)
N <- rep(2, length.out = M)
rho <- rep(TRUE, length.out = M)
.C(`rFriedmanR`, as.integer(r), as.integer(N), as.integer(rho),
as.integer(n), as.integer(M), value = double(n),PACKAGE="SuppDists")$value
}
## use .Defunct function?
## see ~/src/R/R-3.5.1/src/library/base/man/base-defunct.Rd
## suggest package RcppZiggurat instead
#rziggurat <-
#function (n, normal = TRUE, new.start = FALSE, seed = 556677)
#{
# n <- if (length(n) > 1)
# length(n)
# else n
# .C(`ziggR`, val = double(n), as.integer(n), as.integer(normal),
# as.integer(new.start), as.integer(seed),PACKAGE="SuppDists")$val
#}
sFriedman <-
function (r, N)
{
M <- max(length(r), length(N))
r <- rep(r, length.out = M)
N <- rep(N, length.out = M)
rho <- rep(FALSE, length.out = M)
value <- .C(`sFriedmanR`, as.integer(r), as.integer(N), as.integer(rho),
as.integer(M), mn = double(M), med = double(M), mod = double(M),
var = double(M), third = double(M), fourth = double(M),PACKAGE="SuppDists")
aList <- list(title = "Friedman's chi-square", r = r, N = N)
makeStatList(aList, value$mn, value$med, value$var, value$mod,
value$third, value$fourth, -1)
}
sghyper <-
function (a, k, N)
{
M <- max(length(a), length(k), length(N))
a <- rep(a, length.out = M)
k <- rep(k, length.out = M)
N <- rep(N, length.out = M)
value <- .C(`sghyperR`, as.double(a), as.double(k), as.double(N),
as.integer(M), mn = double(M), med = double(M), mod = double(M),
var = double(M), third = double(M), fourth = double(M),PACKAGE="SuppDists")
aList <- list(title = "Generalized Hypergeometric", a = a,
k = k, N = N)
makeStatList(aList, value$mn, value$med, value$var, value$mod,
value$third, value$fourth, -1)
}
sinvGauss <-
function (nu, lambda)
{
N <- max(length(nu), length(lambda))
nu <- rep(nu, length.out = N)
lambda <- rep(lambda, length.out = N)
med <- qinvGauss(0.5, nu, lambda)
nu[nu<=0]<-NA
lambda[lambda<=0]<-NA
factor <- (nu^2)/lambda
var <- nu * factor
k3 <- 3 * var * factor
k4 <- 5 * k3 * factor
mod <- -1.5 * factor + nu * sqrt(1 + 2.25 * (nu/lambda)^2)
third <- k3
fourth <- k4 + 3 * var^2
aList <- list(title = "Inverse Gaussian", nu = nu, lambda = lambda)
makeStatList(aList, nu, med, var, mod, third, fourth, -1)
}
sJohnson <-
function (parms)
{
tfun <- function(x) if (x == "SN")
1
else if (x == "SL")
2
else if (x == "SU")
3
else 4
vecFromList <- function(item, aList) {
if (!is.list(aList[[1]]))
return(aList[[item]])
else {
tVec <- vector(length = 0)
for (i in 1:length(aList)) {
tVec <- append(tVec, (aList[[i]])[[item]])
}
}
tVec
}
gamma <- vecFromList(1, parms)
delta <- vecFromList(2, parms)
xi <- vecFromList(3, parms)
lambda <- vecFromList(4, parms)
type <- vecFromList(5, parms)
type <- sapply(type, tfun)
N <- length(gamma)
value <- .C(`sJohnsonR`, as.double(gamma), as.double(delta),
as.double(xi), as.double(lambda), as.integer(type), as.integer(N),
mn = double(N), med = double(N), mod = double(N), var = double(N),
third = double(N), fourth = double(N),PACKAGE="SuppDists")
aList <- list(title = "Johnson Distribution", gamma = gamma,
delta = delta, xi = xi, lambda = lambda, type = type)
makeStatList(aList, value$mn, value$med, value$var, value$mod,
value$third, value$fourth, -1)
}
sKendall <-
function (N)
{
M <- length(N)
mn <- rep(0, length.out = M)
med <- rep(0, length.out = M)
mod <- rep(0, length.out = M)
third <- rep(0, length.out = M)
var <- (4 * N + 10)/(9 * N * (N - 1))
fourth <- .C(`fourthKendallR`, as.integer(N), as.integer(M),
val = double(M),PACKAGE="SuppDists")$val
aList <- list(title = "Kendall's Tau", N = N)
makeStatList(aList, mn, med, var, mod, third, fourth, -1)
}
sKruskalWallis <-
function (c, N, U)
{
M <- max(length(c), length(N), length(U))
c <- rep(c, length.out = M)
n <- rep(N, length.out = M)
U <- rep(U, length.out = M)
Ns <- rep(FALSE, length.out = M)
value <- .C(`sKruskalWallisR`, as.integer(c), as.integer(n),
as.double(U), as.integer(Ns), as.integer(M), var = double(M),
mod = double(M), third = double(M), fourth = double(M),PACKAGE="SuppDists")
mn <- (c - 1)
aList <- list(title = "Kruskal Wallis", c = c, N = n, U = U)
median <- qKruskalWallis(0.5, c, n, U, Ns)
makeStatList(aList, mn, median, value$var, value$mod, value$third,
value$fourth, -1)
}
smaxFratio <-
function (df, k)
{
N <- max(length(df), length(k))
df <- rep(df, length.out = N)
k <- rep(k, length.out = N)
value <- .C(`smaxFratioR`, as.integer(df), as.integer(k),
as.integer(N), mn = double(N), med = double(N), mod = double(N),
var = double(N), third = double(N), fourth = double(N),PACKAGE="SuppDists")
aList <- list(title = "Maximum F ratio", df = df, k = k)
makeStatList(aList, value$mn, value$med, value$var, value$mod,
value$third, value$fourth, 2)
}
sNormScore <-
function (c, N, U)
{
M <- max(length(c), length(N), length(U))
c <- rep(c, length.out = M)
n <- rep(N, length.out = M)
U <- rep(U, length.out = M)
Ns <- rep(TRUE, length.out = M)
value <- .C(`sKruskalWallisR`, as.integer(c), as.integer(n),
as.double(U), as.integer(Ns), as.integer(M), var = double(M),
mod = double(M), third = double(M), fourth = double(M),PACKAGE="SuppDists")
mn <- (c - 1)
aList <- list(title = "Normal Scores", c = c, N = n, U = U)
median <- qNormScore(0.5, c, n, U)
makeStatList(aList, mn, median, value$var, value$mod, value$third,
value$fourth, -1)
}
sPearson <-
function (N, rho = 0)
{
M <- max(length(rho), length(N))
rho <- rep(rho, length.out = M)
N <- rep(N, length.out = M)
value <- .C(`scorrR`, as.double(rho), as.integer(N), as.integer(M),
mn = double(M), med = double(M), mod = double(M), var = double(M),
third = double(M), fourth = double(M),PACKAGE="SuppDists")
aList <- list(title = "Correlation coefficient", rho = rho,
N = N)
makeStatList(aList, value$mn, value$med, value$var, value$mod,
value$third, value$fourth, -1)
}
sSpearman <-
function (r)
{
M <- length(r)
r <- rep(r, length.out = M)
N <- rep(2, length.out = M)
rho <- rep(TRUE, length.out = M)
value <- .C(`sFriedmanR`, as.integer(r), as.integer(N), as.integer(rho),
as.integer(M), mn = double(M), med = double(M), mod = double(M),
var = double(M), third = double(M), fourth = double(M),PACKAGE="SuppDists")
aList <- list(title = "Spearman's rho", r = r)
makeStatList(aList, value$mn, value$med, value$var, value$mod,
value$third, value$fourth, -1)
}
tghyper <-
function (a, k, N)
{
value <- .C(`tghyperR`, as.double(a), as.double(k), as.double(N),
strn =paste(rep(" ", 128), collapse=""),PACKAGE="SuppDists" )
value$strn
}
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