Bernoulli: Bernoulli Numbers in Arbitrary Precision

In Rmpfr: R MPFR - Multiple Precision Floating-Point Reliable

Bernoulli Numbers in Arbitrary Precision

Description

Computes the Bernoulli numbers in the desired (binary) precision. The computation happens via the zeta function and the formula

B_k = -k \zeta(1 - k),

and hence the only non-zero odd Bernoulli number is B_1 = +1/2. (Another tradition defines it, equally sensibly, as -1/2.)

Usage

Bernoulli(k, precBits = 128)

Arguments

k	non-negative integer vector
precBits	the precision in bits desired.

Value

an mpfr class vector of the same length as k, with i-th component the k[i]-th Bernoulli number.

Author(s)

Martin Maechler

References

https://en.wikipedia.org/wiki/Bernoulli_number

See Also

zeta is used to compute them.

The next version of package gmp is to contain BernoulliQ(), providing exact Bernoulli numbers as big rationals (class "bigq").

Examples

Bernoulli(0:10)
plot(as.numeric(Bernoulli(0:15)), type = "h")

curve(-x*zeta(1-x), -.2, 15.03, n=300,
      main = expression(-x %.% zeta(1-x)))
legend("top", paste(c("even","odd  "), "Bernoulli numbers"),
       pch=c(1,3), col=2, pt.cex=2, inset=1/64)
abline(h=0,v=0, lty=3, col="gray")
k <- 0:15; k[1] <- 1e-4
points(k, -k*zeta(1-k), col=2, cex=2, pch=1+2*(k%%2))

## They pretty much explode for larger k :
k2 <- 2*(1:120)
plot(k2, abs(as.numeric(Bernoulli(k2))), log = "y")
title("Bernoulli numbers exponential growth")

Bernoulli(10000)# - 9.0494239636 * 10^27677

Rmpfr documentation built on Aug. 8, 2023, 5:14 p.m.