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Special: Special Functions of Mathematics

Special

R Documentation

Special Functions of Mathematics

Description

Special mathematical functions related to the beta and gamma functions.

Usage

beta(a, b)
lbeta(a, b)

gamma(x)
lgamma(x)
psigamma(x, deriv = 0)
digamma(x)
trigamma(x)

choose(n, k)
lchoose(n, k)
factorial(x)
lfactorial(x)

Arguments

`a, b`	non-negative numeric vectors.
`x, n`	numeric vectors.
`k, deriv`	integer vectors.

Details

The functions beta and lbeta return the beta function and the natural logarithm of the beta function,

B(a,b) = Γ(a)Γ(b)/Γ(a+b).

The formal definition is

integral_0^1 t^(a-1) (1-t)^(b-1) dt

(Abramowitz and Stegun section 6.2.1, page 258). Note that it is only defined in R for non-negative a and b, and is infinite if either is zero.

The functions gamma and lgamma return the gamma function Γ(x) and the natural logarithm of the absolute value of the gamma function. The gamma function is defined by (Abramowitz and Stegun section 6.1.1, page 255)

Γ(x) = integral_0^Inf t^(x-1) exp(-t) dt

for all real x except zero and negative integers (when NaN is returned). There will be a warning on possible loss of precision for values which are too close (within about 1e-8) to a negative integer less than -10.

factorial(x) (x! for non-negative integer x) is defined to be gamma(x+1) and lfactorial to be lgamma(x+1).

The functions digamma and trigamma return the first and second derivatives of the logarithm of the gamma function. psigamma(x, deriv) (deriv >= 0) computes the deriv-th derivative of ψ(x).

digamma(x) = ψ(x) = d/dx{ln Γ(x)} = Γ'(x) / Γ(x)

ψ and its derivatives, the psigamma() functions, are often called the ‘polygamma’ functions, e.g. in Abramowitz and Stegun (section 6.4.1, page 260); and higher derivatives (deriv = 2:4) have occasionally been called ‘tetragamma’, ‘pentagamma’, and ‘hexagamma’.

The functions choose and lchoose return binomial coefficients and the logarithms of their absolute values. Note that choose(n, k) is defined for all real numbers n and integer k. For k ≥ 1 it is defined as n(n-1)…(n-k+1) / k!, as 1 for k = 0 and as 0 for negative k. Non-integer values of k are rounded to an integer, with a warning.
choose(*, k) uses direct arithmetic (instead of [l]gamma calls) for small k, for speed and accuracy reasons. Note the function combn (package utils) for enumeration of all possible combinations.

The gamma, lgamma, digamma and trigamma functions are internal generic primitive functions: methods can be defined for them individually or via the Math group generic.

Source

gamma, lgamma, beta and lbeta are based on C translations of Fortran subroutines by W. Fullerton of Los Alamos Scientific Laboratory (now available as part of SLATEC).

digamma, trigamma and psigamma are based on

Amos, D. E. (1983). A portable Fortran subroutine for derivatives of the psi function, Algorithm 610, ACM Transactions on Mathematical Software 9(4), 494–502.

References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole. (For gamma and lgamma.)

Abramowitz, M. and Stegun, I. A. (1972) Handbook of Mathematical Functions. New York: Dover. https://en.wikipedia.org/wiki/Abramowitz_and_Stegun provides links to the full text which is in public domain.
Chapter 6: Gamma and Related Functions.

Examples

require(graphics)

choose(5, 2)
for (n in 0:10) print(choose(n, k = 0:n))

factorial(100)
lfactorial(10000)

## gamma has 1st order poles at 0, -1, -2, ...
## this will generate loss of precision warnings, so turn off
op <- options("warn")
options(warn = -1)
x <- sort(c(seq(-3, 4, length.out = 201), outer(0:-3, (-1:1)*1e-6, "+")))
plot(x, gamma(x), ylim = c(-20,20), col = "red", type = "l", lwd = 2,
     main = expression(Gamma(x)))
abline(h = 0, v = -3:0, lty = 3, col = "midnightblue")
options(op)

x <- seq(0.1, 4, length.out = 201); dx <- diff(x)[1]
par(mfrow = c(2, 3))
for (ch in c("", "l","di","tri","tetra","penta")) {
  is.deriv <- nchar(ch) >= 2
  nm <- paste0(ch, "gamma")
  if (is.deriv) {
    dy <- diff(y) / dx # finite difference
    der <- which(ch == c("di","tri","tetra","penta")) - 1
    nm2 <- paste0("psigamma(*, deriv = ", der,")")
    nm  <- if(der >= 2) nm2 else paste(nm, nm2, sep = " ==\n")
    y <- psigamma(x, deriv = der)
  } else {
    y <- get(nm)(x)
  }
  plot(x, y, type = "l", main = nm, col = "red")
  abline(h = 0, col = "lightgray")
  if (is.deriv) lines(x[-1], dy, col = "blue", lty = 2)
}
par(mfrow = c(1, 1))

## "Extended" Pascal triangle:
fN <- function(n) formatC(n, width=2)
for (n in -4:10) {
    cat(fN(n),":", fN(choose(n, k = -2:max(3, n+2))))
    cat("\n")
}

## R code version of choose()  [simplistic; warning for k < 0]:
mychoose <- function(r, k)
    ifelse(k <= 0, (k == 0),
           sapply(k, function(k) prod(r:(r-k+1))) / factorial(k))
k <- -1:6
cbind(k = k, choose(1/2, k), mychoose(1/2, k))

## Binomial theorem for n = 1/2 ;
## sqrt(1+x) = (1+x)^(1/2) = sum_{k=0}^Inf  choose(1/2, k) * x^k :
k <- 0:10 # 10 is sufficient for ~ 9 digit precision:
sqrt(1.25)
sum(choose(1/2, k)* .25^k)