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####    d|ensity
####    p|robability (cumulative)
####    q|uantile
####    r|andom number generation
####
####    Functions for  ``d/p/q/r''

.ptime <- proc.time()
F <- FALSE
T <- TRUE

###-- these are identical in ./arith-true.R ["fixme": use source(..)]
opt.conformance <- 0
Meps <- .Machine $ double.eps
xMax <- .Machine $ double.xmax
options(rErr.eps = 1e-30)
rErr <- function(approx, true, eps = .Options$rErr.eps)
{
    if(is.null(eps)) { eps <- 1e-30; options(rErr.eps = eps) }
    ifelse(Mod(true) >= eps,
       1 - approx / true, # relative error
       true - approx)     # absolute error (e.g. when true=0)
}
## Short cut:
All.eq <- function(x,y) all.equal.numeric(x,y, tolerance = 100*.Machine$double.eps)

if(!interactive())
    .Random.seed <- c(0,rep(7654, 3))

## The prefixes of ALL the PDQ & R functions
PDQRinteg <- c("binom", "geom", "hyper", "nbinom", "pois","signrank","wilcox")
PDQR <- c(PDQRinteg, "beta", "cauchy", "chisq", "exp", "f", "gamma",
      "lnorm", "logis", "norm", "t","unif","weibull")
PQonly <- c("tukey")

###--- Discrete Distributions --- Consistency Checks  pZZ = cumsum(dZZ)

##for(pre in PDQRinteg) { n <- paste("d",pre,sep=""); cat(n,": "); str(get(n))}

##__ 1. Binomial __

## Cumulative Binomial '==' Cumulative F :
## Abramowitz & Stegun, p.945-6;  26.5.24  AND  26.5.28 :
n0 <- 50; n1 <- 16; n2 <- 20; n3 <- 8
for(n in rbinom(n1, size = 2*n0, p = .4)) {
    cat("n=",n,": ")
    for(p in c(0,1,rbeta(n2, 2,4))) {
    cat(".")
    for(k in rbinom(n3, size = n,  prob = runif(1))) {
        ## For X ~ Bin(n,p), compute 1 - P[X > k] = P[X <= k] in three ways:
        tst1 <- all.equal(       pbinom(0:k, size = n, prob = p),
                  cumsum(dbinom(0:k, size = n, prob = p)))
        tst <- all.equal(if(k==n || p==0) 1 else
                 pf((k+1)/(n-k)*(1-p)/p, df1=2*(n-k), df2=2*(k+1)),
                 sum(dbinom(0:k, size = n, prob = p)))
        if(!(is.logical(tst1) && tst1) ||
           !(is.logical(tst)  && tst ) ) {
        cat("n=", n,"; p =",format(p),".  k =",k)
        if(!is.logical(tst1)) cat("; tst1=",tst1)
        if(!is.logical(tst )) cat("; tst=", tst)
        cat("\n")
        }
    }
    }
    cat("\n")
}

##__ 2. Geometric __
for(pr in seq(0,1,len=15)) {
    print(All.eq((dg <- dgeom(0:10, pr)),
         pr * (1-pr)^(0:10)))
    print(All.eq(cumsum(dg), pgeom(0:10, pr)))
}

##__ 3. Hypergeometric __

m <- 10; n <- 7
for(k in 2:m) {
    x <- 0:(k+1)
    print(All.eq(phyper(x, m, n, k), cumsum(dhyper(x, m, n, k))))
}

##__ 4. Negative Binomial __

## PR #842
for(size in seq(0.8,2, by=.1))
    print(all.equal(cumsum(dnbinom(0:7, size, .5)),
               pnbinom(0:7, size, .5)))
All.eq(pnbinom(c(1,3), .9, .5), c(0.777035760338812, 0.946945347071519))

##__ 5. Poisson __

all(dpois(0:5,0)       == c(1, rep(0,5)))
all(dpois(0:5,0, log=TRUE) == c(0, rep(-Inf, 5)))

## Cumulative Poisson '==' Cumulative Chi^2 :
## Abramowitz & Stegun, p.941 :  26.4.21 (26.4.2)
n1 <- 20; n2 <- 16
for(lambda in rexp(n1))
    for(k in rpois(n2, lambda)) {
    tst <- all.equal(1 - pchisq(2*lambda, 2*(1+ 0:k)),
             pp <- cumsum(dpois(0:k, lambda=lambda)), tol= 100*Meps)
    if(!(is.logical(tst) && tst))
        cat("lambda=", format(lambda),".  k =",k, " --> tst=", tst,"\n")
    tst2 <- all.equal(pp, ppois(0:k, lambda=lambda), tol = 100*Meps)
    if(!(is.logical(tst2) && tst2))
        cat("lambda=", format(lambda),".  k =",k, " --> tst2=", tst2,"\n")
    tst3 <- all.equal(1 - pp, ppois(0:k, lambda=lambda, lower.tail=FALSE))
    if(!(is.logical(tst3) && tst3))
        cat("lambda=", format(lambda),".  k =",k, " --> tst3=", tst3,"\n")
    }


##__ 6. SignRank __
for(n in rpois(32, lam=8)) {
    x <- -1:(n + 4)
    eq <- All.eq(psignrank(x, n), cumsum(dsignrank(x, n)))
    if(!is.logical(eq) || !eq) print(eq)
}

##__ 7. Wilcoxon (symmetry & cumulative) __
is.sym <- TRUE
for(n in rpois(5, lam=6))
    for(m in rpois(15, lam=8)) {
    x <- -1:(n*m + 1)
    fx <- dwilcox(x, n, m)
    Fx <- pwilcox(x, n, m)
    is.sym <- is.sym & all(fx == dwilcox(x, m, n))
    eq <- All.eq(Fx, cumsum(fx))
    if(!is.logical(eq) || !eq) print(eq)
    }
is.sym


###-------- Continuous Distributions ----------

##---  Gamma (incl. central chi^2) Density :
x <- round(rgamma(100, shape = 2),2)
for(sh in round(rlnorm(30),2)) {
    Ga <- gamma(sh)
    for(sig in round(rlnorm(30),2)) {
    tst <- all.equal((d1 <- dgamma(  x,   shape = sh, scale = sig)),
             (d2 <- dgamma(x/sig, shape = sh, scale = 1) / sig),
             tol = 1e-14)## __ad interim__ was 1e-15
    if(!(is.logical(tst) && tst))
        cat("ERROR: dgamma() doesn't scale:",tst,"\n",
        "  x =", formatC(x),"\n  shape,scale=",formatC(c(sh, sig)),"\n")
    tst <- All.eq(d1, (d3 <- 1/(Ga * sig^sh) * x^(sh-1) * exp(-x/sig)))
    if(!(is.logical(tst) && tst))
        cat("NOT Equal:",tst,"\n x =", formatC(x),
        "\n  shape,scale=",formatC(c(sh, sig)),"\n")
    }
}
pgamma(1,Inf,scale=Inf) == 0
all(is.nan(c(pgamma(Inf,1,scale=Inf), pgamma(Inf,Inf,scale=1), pgamma(Inf,Inf,scale=Inf))))
pgamma(Inf,1,scale=xMax) == 1 && pgamma(xMax,1,scale=Inf) == 0
##-- non central Chi^2 :
xB <- c(2000,1e6,1e50,Inf)
for(df in c(0.1, 1, 10))
    for(ncp in c(0, 1, 10, 100)) stopifnot(pchisq(xB, df=df, ncp=ncp) == 1)
all.equal(qchisq(0.025,31,ncp=1,lower.tail=FALSE),# inf.loop PR#875
          49.77662465615, tol= 1e-11)
## p ~= 1 (<==> 1-p ~= 0) -- gave infinite loop in R <= 1.8.1 -- PR#6421
psml <- 2^-(10:54)
q0 <- qchisq(psml,    df=1.2, ncp=10, lower.tail=FALSE)
q1 <- qchisq(1 -psml, df=1.2, ncp=10)
p0 <- pchisq(q0, df=1.2, ncp=10, lower.tail=FALSE)
p1 <- pchisq(q1, df=1.2, ncp=10, lower.tail=FALSE)
iO <- 1:10
all.equal(q0[iO], q1[iO])
all.equal(p0[iO], psml[iO], tol = 0.08)# bad tol (0.0744 on 386-Linux).

##--- Beta (need more):

## big a & b (PR #643)
summary(a <- rlnorm(20, 5.5))
summary(b <- rlnorm(20, 6.5))
pab <- expand.grid(seq(0,1,by=.1), a, b)
p <- pab[,1]; a <- pab[,2]; b <- pab[,3]
all.equal(dbeta(p,a,b), exp(pab <- dbeta(p,a,b, log = TRUE)), tol = 1e-11)
sample(pab, 50)


##--- Normal (& Lognormal) :

qnorm(0) == -Inf && qnorm(-Inf, log = TRUE) == -Inf
qnorm(1) ==  Inf && qnorm(0, log = TRUE) == Inf

is.nan(qnorm(1.1)) &&
is.nan(qnorm(-.1)) # + warn

x <- c(-Inf, -1e100, 1:6, 1e200, Inf)
rbind(d.s0 =dnorm(x,3,s=0),   p.s0 = pnorm(x,3,s=0),
      d.sI =dnorm(x,3,s=Inf), p.sI = pnorm(x,3,s=Inf))

## 3 Test data from Wichura (1988) :
all.equal(qnorm(c( 0.25,  .001,  1e-20)),
      c(-0.6744897501960817, -3.090232306167814, -9.262340089798408),
      tol = 1e-15)
# extreme tail -- available on log scale only:
all.equal(qnorm(-1e5, log = TRUE), -447.1974945)

z <- rnorm(1000); all.equal(pnorm(z),  1 - pnorm(-z), tol= 1e-15)
z <- c(-Inf,Inf,NA,NaN, rt(1000, df=2))
z.ok <- z > -37.5 | !is.finite(z)
for(df in 1:10) if(!is.logical(all.equal(pt(z, df), 1 - pt(-z,df), tol= 1e-15)))
    cat("ERROR -- df = ", df, "\n")
All.eq(pz <- pnorm(z), 1 - pnorm(z, lower=FALSE))
All.eq(pz,       pnorm(-z, lower=FALSE))
All.eq(log(pz[z.ok]),  pnorm(z[z.ok], log=TRUE))
y <- seq(-70,0, by = 10)
cbind(y, "log(pnorm(y))"= log(pnorm(y)), "pnorm(y, log=T)"= pnorm(y, log=TRUE))
y <- c(1:15, seq(20,40, by=5))
cbind(y, "log(pnorm(y))"= log(pnorm(y)), "pnorm(y, log=T)"= pnorm(y, log=TRUE),
      "log(pnorm(-y))"= log(pnorm(-y)), "pnorm(-y, log=T)"= pnorm(-y, log=TRUE))
## Symmetry:
y <- c(1:50,10^c(3:10,20,50,150,250))
y <- c(-y,0,y)
for(L in c(FALSE,TRUE))
    stopifnot(identical(pnorm(-y, log= L),
            pnorm(+y, log= L, lower=FALSE)))

## Log norm
All.eq(pz, plnorm(exp(z)))


###==========  p <-> q  Inversion consistency =====================
ok <- 1e-5 < pz & pz < 1 - 1e-5
all.equal(z[ok], qnorm(pz[ok]), tol= 1e-12)

###===== Random numbers -- first, just output:

.Random.seed <- c(0, 17292, 29447, 24113)
n <- 20
## for(pre in PDQR) { n <- paste("r",pre,sep=""); cat(n,": "); str(get(n))}
(Rbeta    <- rbeta    (n, shape1 = .8, shape2 = 2) )
(Rbinom   <- rbinom   (n, size = 55, prob = pi/16) )
(Rcauchy  <- rcauchy  (n, location = 12, scale = 2) )
(Rchisq   <- rchisq   (n, df = 3) )
(Rexp     <- rexp     (n, rate = 2) )
(Rf   <- rf       (n, df1 = 12, df2 = 6) )
(Rgamma   <- rgamma   (n, shape = 2, scale = 5) )
(Rgeom    <- rgeom    (n, prob = pi/16) )
(Rhyper   <- rhyper   (n, m = 40, n = 30, k = 20) )
(Rlnorm   <- rlnorm   (n, meanlog = -1, sdlog = 3) )
(Rlogis   <- rlogis   (n, location = 12, scale = 2) )
(Rnbinom  <- rnbinom  (n, size = 7, prob = .01) )
(Rnorm    <- rnorm    (n, mean = -1, sd = 3) )
(Rpois    <- rpois    (n, lambda = 12) )
(Rsignrank<- rsignrank(n, n = 47) )
(Rt   <- rt       (n, df = 11) )
## Rt2 below (to preserve the following random numbers!)
(Runif    <- runif    (n, min = .2, max = 2) )
(Rweibull <- rweibull (n, shape = 3, scale = 2) )
(Rwilcox  <- rwilcox  (n, m = 13, n = 17) )
(Rt2      <- rt       (n, df = 1.01))

(Pbeta    <- pbeta    (Rbeta, shape1 = .8, shape2 = 2) )
(Pbinom   <- pbinom   (Rbinom, size = 55, prob = pi/16) )
(Pcauchy  <- pcauchy  (Rcauchy, location = 12, scale = 2) )
(Pchisq   <- pchisq   (Rchisq, df = 3) )
(Pexp     <- pexp     (Rexp, rate = 2) )
(Pf   <- pf       (Rf, df1 = 12, df2 = 6) )
(Pgamma   <- pgamma   (Rgamma, shape = 2, scale = 5) )
(Pgeom    <- pgeom    (Rgeom, prob = pi/16) )
(Phyper   <- phyper   (Rhyper, m = 40, n = 30, k = 20) )
(Plnorm   <- plnorm   (Rlnorm, meanlog = -1, sdlog = 3) )
(Plogis   <- plogis   (Rlogis, location = 12, scale = 2) )
(Pnbinom  <- pnbinom  (Rnbinom, size = 7, prob = .01) )
(Pnorm    <- pnorm    (Rnorm, mean = -1, sd = 3) )
(Ppois    <- ppois    (Rpois, lambda = 12) )
(Psignrank<- psignrank(Rsignrank, n = 47) )
(Pt   <- pt       (Rt,  df = 11) )
(Pt2      <- pt       (Rt2, df = 1.01) )
(Punif    <- punif    (Runif, min = .2, max = 2) )
(Pweibull <- pweibull (Rweibull, shape = 3, scale = 2) )
(Pwilcox  <- pwilcox  (Rwilcox, m = 13, n = 17) )

dbeta    (Rbeta, shape1 = .8, shape2 = 2)
dbinom   (Rbinom, size = 55, prob = pi/16)
dcauchy  (Rcauchy, location = 12, scale = 2)
dchisq   (Rchisq, df = 3)
dexp     (Rexp, rate = 2)
df   (Rf, df1 = 12, df2 = 6)
dgamma   (Rgamma, shape = 2, scale = 5)
dgeom    (Rgeom, prob = pi/16)
dhyper   (Rhyper, m = 40, n = 30, k = 20)
dlnorm   (Rlnorm, meanlog = -1, sdlog = 3)
dlogis   (Rlogis, location = 12, scale = 2)
dnbinom  (Rnbinom, size = 7, prob = .01)
dnorm    (Rnorm, mean = -1, sd = 3)
dpois    (Rpois, lambda = 12)
dsignrank(Rsignrank, n = 47)
dt   (Rt, df = 11)
dunif    (Runif, min = .2, max = 2)
dweibull (Rweibull, shape = 3, scale = 2)
dwilcox  (Rwilcox, m = 13, n = 17)

## Check q*(p*(.)) = identity
All.eq(Rbeta,     qbeta    (Pbeta, shape1 = .8, shape2 = 2))
All.eq(Rbinom,    qbinom   (Pbinom, size = 55, prob = pi/16))
All.eq(Rcauchy,   qcauchy  (Pcauchy, location = 12, scale = 2))
All.eq(Rchisq,    qchisq   (Pchisq, df = 3))
All.eq(Rexp,      qexp     (Pexp, rate = 2))
All.eq(Rf,    qf       (Pf, df1 = 12, df2 = 6))
All.eq(Rgamma,    qgamma   (Pgamma, shape = 2, scale = 5))
All.eq(Rgeom,     qgeom    (Pgeom, prob = pi/16))
All.eq(Rhyper,    qhyper   (Phyper, m = 40, n = 30, k = 20))
All.eq(Rlnorm,    qlnorm   (Plnorm, meanlog = -1, sdlog = 3))
All.eq(Rlogis,    qlogis   (Plogis, location = 12, scale = 2))
All.eq(Rnbinom,   qnbinom  (Pnbinom, size = 7, prob = .01))
All.eq(Rnorm,     qnorm    (Pnorm, mean = -1, sd = 3))
All.eq(Rpois,     qpois    (Ppois, lambda = 12))
All.eq(Rsignrank, qsignrank(Psignrank, n = 47))
All.eq(Rt,    qt       (Pt,  df = 11))
all.equal(Rt2,    qt       (Pt2, df = 1.01), tol = 1e-2)
All.eq(Runif,     qunif    (Punif, min = .2, max = 2))
All.eq(Rweibull,  qweibull (Pweibull, shape = 3, scale = 2))
All.eq(Rwilcox,   qwilcox  (Pwilcox, m = 13, n = 17))

## Same with "upper tail":
All.eq(Rbeta,     qbeta    (1- Pbeta, shape1 = .8, shape2 = 2, lower=F))
All.eq(Rbinom,    qbinom   (1- Pbinom, size = 55, prob = pi/16, lower=F))
All.eq(Rcauchy,   qcauchy  (1- Pcauchy, location = 12, scale = 2, lower=F))
All.eq(Rchisq,    qchisq   (1- Pchisq, df = 3, lower=F))
All.eq(Rexp,      qexp     (1- Pexp, rate = 2, lower=F))
All.eq(Rf,    qf       (1- Pf, df1 = 12, df2 = 6, lower=F))
All.eq(Rgamma,    qgamma   (1- Pgamma, shape = 2, scale = 5, lower=F))
All.eq(Rgeom,     qgeom    (1- Pgeom, prob = pi/16, lower=F))
All.eq(Rhyper,    qhyper   (1- Phyper, m = 40, n = 30, k = 20, lower=F))
All.eq(Rlnorm,    qlnorm   (1- Plnorm, meanlog = -1, sdlog = 3, lower=F))
All.eq(Rlogis,    qlogis   (1- Plogis, location = 12, scale = 2, lower=F))
All.eq(Rnbinom,   qnbinom  (1- Pnbinom, size = 7, prob = .01, lower=F))
All.eq(Rnorm,     qnorm    (1- Pnorm, mean = -1, sd = 3,lower=F))
All.eq(Rpois,     qpois    (1- Ppois, lambda = 12, lower=F))
All.eq(Rsignrank, qsignrank(1- Psignrank, n = 47, lower=F))
All.eq(Rt,    qt       (1- Pt,  df = 11,   lower=F))
all.equal(Rt2,    qt       (1- Pt2, df = 1.01, lower=F), tol = 1e-2)
All.eq(Runif,     qunif    (1- Punif, min = .2, max = 2, lower=F))
All.eq(Rweibull,  qweibull (1- Pweibull, shape = 3, scale = 2, lower=F))
All.eq(Rwilcox,   qwilcox  (1- Pwilcox, m = 13, n = 17, lower=F))

## Check q*(p* ( log ), log) = identity
All.eq(Rbeta,     qbeta    (log(Pbeta), shape1 = .8, shape2 = 2, log=TRUE))
All.eq(Rbinom,    qbinom   (log(Pbinom), size = 55, prob = pi/16, log=TRUE))
All.eq(Rcauchy,   qcauchy  (log(Pcauchy), location = 12, scale = 2, log=TRUE))
all.equal(Rchisq,    qchisq   (log(Pchisq), df = 3, log=TRUE),tol=1e-14)
All.eq(Rexp,      qexp     (log(Pexp), rate = 2, log=TRUE))
All.eq(Rf,    qf       (log(Pf), df1= 12, df2= 6, log=TRUE))
All.eq(Rgamma,    qgamma   (log(Pgamma), shape = 2, scale = 5, log=TRUE))
All.eq(Rgeom,     qgeom    (log(Pgeom), prob = pi/16, log=TRUE))
All.eq(Rhyper,    qhyper   (log(Phyper), m = 40, n = 30, k = 20, log=TRUE))
All.eq(Rlnorm,    qlnorm   (log(Plnorm), meanlog = -1, sdlog = 3, log=TRUE))
All.eq(Rlogis,    qlogis   (log(Plogis), location = 12, scale = 2, log=TRUE))
All.eq(Rnbinom,   qnbinom  (log(Pnbinom), size = 7, prob = .01, log=TRUE))
All.eq(Rnorm,     qnorm    (log(Pnorm), mean = -1, sd = 3, log=TRUE))
All.eq(Rpois,     qpois    (log(Ppois), lambda = 12, log=TRUE))
All.eq(Rsignrank, qsignrank(log(Psignrank), n = 47, log=TRUE))
All.eq(Rt,    qt       (log(Pt), df = 11, log=TRUE))
all.equal(Rt2,    qt       (log(Pt2), df = 1.01, log=TRUE), tol = 1e-2)
All.eq(Runif,     qunif    (log(Punif), min = .2, max = 2, log=TRUE))
All.eq(Rweibull,  qweibull (log(Pweibull), shape = 3, scale = 2, log=TRUE))
All.eq(Rwilcox,   qwilcox  (log(Pwilcox), m = 13, n = 17, log=TRUE))

## same q*(p* (log) log) with upper tail:

All.eq(Rbeta,     qbeta    (log(1- Pbeta), shape1 = .8, shape2 = 2, lower=F, log=T))
All.eq(Rbinom,    qbinom   (log(1- Pbinom), size = 55, prob = pi/16, lower=F, log=T))
All.eq(Rcauchy,   qcauchy  (log(1- Pcauchy), location = 12, scale = 2, lower=F, log=T))
All.eq(Rchisq,    qchisq   (log(1- Pchisq), df = 3, lower=F, log=T))
All.eq(Rexp,      qexp     (log(1- Pexp), rate = 2, lower=F, log=T))
All.eq(Rf,    qf       (log(1- Pf), df1 = 12, df2 = 6, lower=F, log=T))
All.eq(Rgamma,    qgamma   (log(1- Pgamma), shape = 2, scale = 5, lower=F, log=T))
All.eq(Rgeom,     qgeom    (log(1- Pgeom), prob = pi/16, lower=F, log=T))
All.eq(Rhyper,    qhyper   (log(1- Phyper), m = 40, n = 30, k = 20, lower=F, log=T))
All.eq(Rlnorm,    qlnorm   (log(1- Plnorm), meanlog = -1, sdlog = 3, lower=F, log=T))
All.eq(Rlogis,    qlogis   (log(1- Plogis), location = 12, scale = 2, lower=F, log=T))
All.eq(Rnbinom,   qnbinom  (log(1- Pnbinom), size = 7, prob = .01, lower=F, log=T))
All.eq(Rnorm,     qnorm    (log(1- Pnorm), mean = -1, sd = 3, lower=F, log=T))
All.eq(Rpois,     qpois    (log(1- Ppois), lambda = 12, lower=F, log=T))
All.eq(Rsignrank, qsignrank(log(1- Psignrank), n = 47, lower=F, log=T))
All.eq(Rt,    qt       (log(1- Pt ), df = 11,   lower=F, log=T))
all.equal(Rt2,    qt       (log(1- Pt2), df = 1.01, lower=F, log=T), tol = 1e-2)
All.eq(Runif,     qunif    (log(1- Punif), min = .2, max = 2, lower=F, log=T))
All.eq(Rweibull,  qweibull (log(1- Pweibull), shape = 3, scale = 2, lower=F, log=T))
All.eq(Rwilcox,   qwilcox  (log(1- Pwilcox), m = 13, n = 17, lower=F, log=T))


## Check log( upper.tail ):
All.eq(log(1 - Pbeta),     pbeta    (Rbeta, shape1 = .8, shape2 = 2, lower=F, log=T))
All.eq(log(1 - Pbinom),    pbinom   (Rbinom, size = 55, prob = pi/16, lower=F, log=T))
All.eq(log(1 - Pcauchy),   pcauchy  (Rcauchy, location = 12, scale = 2, lower=F, log=T))
All.eq(log(1 - Pchisq),    pchisq   (Rchisq, df = 3, lower=F, log=T))
All.eq(log(1 - Pexp),      pexp     (Rexp, rate = 2, lower=F, log=T))
All.eq(log(1 - Pf),    pf       (Rf, df1 = 12, df2 = 6, lower=F, log=T))
All.eq(log(1 - Pgamma),    pgamma   (Rgamma, shape = 2, scale = 5, lower=F, log=T))
All.eq(log(1 - Pgeom),     pgeom    (Rgeom, prob = pi/16, lower=F, log=T))
All.eq(log(1 - Phyper),    phyper   (Rhyper, m = 40, n = 30, k = 20, lower=F, log=T))
All.eq(log(1 - Plnorm),    plnorm   (Rlnorm, meanlog = -1, sdlog = 3, lower=F, log=T))
All.eq(log(1 - Plogis),    plogis   (Rlogis, location = 12, scale = 2, lower=F, log=T))
All.eq(log(1 - Pnbinom),   pnbinom  (Rnbinom, size = 7, prob = .01, lower=F, log=T))
All.eq(log(1 - Pnorm),     pnorm    (Rnorm, mean = -1, sd = 3, lower=F, log=T))
All.eq(log(1 - Ppois),     ppois    (Rpois, lambda = 12, lower=F, log=T))
All.eq(log(1 - Psignrank), psignrank(Rsignrank, n = 47, lower=F, log=T))
All.eq(log(1 - Pt),    pt       (Rt, df = 11,   lower=F, log=T))
All.eq(log(1 - Pt2),       pt       (Rt2,df = 1.01, lower=F, log=T))
All.eq(log(1 - Punif),     punif    (Runif, min = .2, max = 2, lower=F, log=T))
All.eq(log(1 - Pweibull),  pweibull (Rweibull, shape = 3, scale = 2, lower=F, log=T))
All.eq(log(1 - Pwilcox),   pwilcox  (Rwilcox, m = 13, n = 17, lower=F, log=T))

cat("Time elapsed: ", proc.time() - .ptime,"\n")