lgamma1p: Accurate 'log(gamma(a+1))'

In DPQ: Density, Probability, Quantile ('DPQ') Computations

Accurate log(gamma(a+1))

Description

Compute

l\Gamma_1(a) := \log\Gamma(a+1) = \log(a\cdot \Gamma(a)) = \log a + \log \Gamma(a),

which is “in principle” the same as log(gamma(a+1)) or lgamma(a+1), accurately also for (very) small a (0 < a < 0.5).

Usage

lgamma1p (a, tol_logcf = 1e-14, f.tol = 1, ...)	
lgamma1p.(a, cutoff.a = 1e-6, k = 3)		
lgamma1p_series(x, k)               		
lgamma1pC(x)                        		

Arguments

a, x	a numeric vector.
tol_logcf	for lgamma1p(): a non-negative number passed to logcf() (and log1pmx() which calls logcf()).
f.tol	numeric (factor) used in log1pmx(*, tol_logcf = f.tol * tol_logcf).
...	further optional arguments passed on to log1pmx().
cutoff.a	for lgamma1p.(): a positive number indicating the cutoff to switch from ...
k	an integer, the number of terms in the series expansion used internally; currently for lgamma1p.(): k \le 3 lgamma1p_series(): k \le 15

Details

lgamma1p() is an R translation of the function (in Fortran) in Didonato and Morris (1992) which uses a 40-degree polynomial approximation.

lgamma1p.(u) for small |u| uses up to 4 terms of

\Gamma(1+u) = 1 + u*(-\gamma_E + a_0 u + a_1 u^2 + a_2 u^3) + O(u^5),

where a_0 := (\psi'(1) + \psi(1)^2)/2 = (\pi^2/6 + \gamma_E^2)/2, and a_1 und a_2 are similarly determined. Then log1p(.) of the \Gamma(1+u) - 1 approximation above is used.

lgamma1p_series(x, k) is a Taylor series approximation of order k, directly of l\Gamma_1(a) := \log \Gamma(a+1) (mostly via Maple), which starts as -\gamma_E x + \pi^2 x^2/ 12 + \dots, where \gamma_E is Euler's constant 0.5772156649.

lgamma1pC() is an interface to R's C API (‘Mathlib’ / ‘Rmath.h’) function lgamma1p().

Value

a numeric vector with the same attributes as a.

Author(s)

Morten Welinder (C code of Jan 2005, see R's bug issue \Sexpr[results=rd]{tools:::Rd_expr_PR(7307)}) for lgamma1p().

Martin Maechler, notably for lgamma1p_series() which works with package Rmpfr but otherwise may be much less accurate than Morten's 40 term series!

References

Didonato, A. and Morris, A., Jr, (1992) Algorithm 708: Significant digit computation of the incomplete beta function ratios. ACM Transactions on Mathematical Software, 18, 360–373; see also pbeta.

See Also

Yet another algorithm, fully double precision accurate in [-0.2, 1.25], is provided by gamln1().

log1pmx, log1p, pbeta.

Examples

curve(lgamma1p, -1.25, 5, n=1001, col=2, lwd=2)
abline(h=0, v=-1:0, lty=c(2,3,2), lwd=c(1, 1/2,1))
for(k in 1:15)
  curve(lgamma1p_series(x, k=k), add=TRUE, col=adjustcolor(paste0("gray",25+k*4), 2/3), lty = 3)

curve(lgamma1p, -0.25, 1.25, n=1001, col=2, lwd=2)
abline(h=0, v=0, lty=2)
for(k in 1:15)
  curve(lgamma1p_series(x, k=k), add=TRUE, col=adjustcolor("gray20", 2/3), lty = 3)

curve(-log(x*gamma(x)), 1e-30, .8, log="xy", col="gray50", lwd = 3,
      axes = FALSE, ylim = c(1e-30,1)) # underflows to zero at x ~= 1e-16
eaxGrid <- function(at.x = 10^(1-4*(0:8)), at.y = at.x) {
    sfsmisc::eaxis(1, sub10 = c(-2, 2), nintLog=16)
    sfsmisc::eaxis(2, sub10 = 2, nintLog=16)
    abline(h = at.y, v = at.x, col = "lightgray", lty = "dotted")
}
eaxGrid()
curve(-lgamma( 1+x), add=TRUE, col="red2", lwd=1/2)# underflows even earlier
curve(-lgamma1p (x), add=TRUE, col="blue") -> lgxy
curve(-lgamma1p.(x), add=TRUE, col=adjustcolor("forest green",1/4),
      lwd = 5, lty = 2)
for(k in 1:15)
  curve(-lgamma1p_series(x, k=k), add=TRUE, col=paste0("gray",80-k*4), lty = 3)
stopifnot(with(lgxy, all.equal(y, -lgamma1pC(x))))

if(requireNamespace("Rmpfr")) { # accuracy comparisons, originally from  ../tests/qgamma-ex.R
    x <- 2^(-(500:11)/8)
    x. <- Rmpfr::mpfr(x, 200)
    ## versions of lgamma1p(x) := lgamma(1+x)
    ## lgamma1p(x) = log gamma(x+1) = log (x * gamma(x)) = log(x) + lgamma(x)
    xct. <- log(x.  * gamma(x.)) # using  MPFR  arithmetic .. no overflow/underflow ...
    xc2. <- log(x.) + lgamma(x.) #  (ditto)

    AllEq <- function(target, current, ...)
        Rmpfr::all.equal(target, current, ...,
                         formatFUN = function(x, ...) Rmpfr::format(x, digits = 9))
    print(AllEq(xct., xc2., tol = 0)) # 2e-57
    rr <- vapply(1:15, function(k) lgamma1p_series(x, k=k), x)
    colnames(rr) <- paste0("k=",1:15)
    relEr <- Rmpfr::asNumeric(sfsmisc::relErrV(xct., rr))
    ## rel.error of direct simple computation:
    relE.D <- Rmpfr::asNumeric(sfsmisc::relErrV(xct., lgamma(1+x)))

    matplot(x, abs(relEr), log="xy", type="l", axes = FALSE,
            main = "|rel.Err(.)| for lgamma(1+x) =~= lgamma1p_series(x, k = 1:15)")
    eaxGrid()
    p2 <- -(53:52); twp <- 2^p2; labL <- lapply(p2, function(p) substitute(2^E, list(E=p)))
    abline(h = twp, lty=3)
    axis(4, at=twp, las=2, line=-1, labels=as.expression(labL), col=NA,col.ticks=NA)
    legend("topleft", paste("k =", 1:15), ncol=3, col=1:6, lty=1:5, bty="n")
    lines(x, abs(relE.D), col = adjustcolor(2, 2/3), lwd=2)
    legend("top", "lgamma(1+x)", col=2, lwd=2)

    ## zoom in:
    matplot(x, abs(relEr), log="xy", type="l", axes = FALSE,
            xlim = c(1e-5, 0.1), ylim = c(1e-17, 1e-10),
            main = "|rel.Err(.)| for lgamma(1+x) =~= lgamma1p_series(x, k = 1:15)")
    eaxGrid(10^(-5:1), 10^-(17:10))
    abline(h = twp, lty=3)
    axis(4, at=twp, las=2, line=-1, labels=as.expression(labL), col=NA,col.ticks=NA)
    legend("topleft", paste("k =", 1:15), ncol=3, col=1:6, lty=1:5, bty="n")
    lines(x, abs(relE.D), col = adjustcolor(2, 2/3), lwd=2)
    legend("right", "lgamma(1+x)", col=2, lwd=2)

} # Rmpfr only

DPQ documentation built on Nov. 3, 2024, 3 a.m.