trCCH {BAS} | R Documentation |
Truncated Compound Confluent Hypergeometric function
Description
Compute the Truncated Confluent Hypergeometric function from Li and Clyde (2018) which is the normalizing constant in the tcch density of Gordy (1998) with integral representation:
Usage
trCCH(a, b, r, s, v, k, log = FALSE)
Arguments
a |
a > 0 |
b |
b > 0 |
r |
r >= 0 |
s |
arbitrary |
v |
0 < v |
k |
arbitrary |
log |
logical indicating whether to return values on the log scale; useful for Bayes Factor calculations |
Details
tr.cch(a,b,r,s,v,k) = Int_0^1/v u^(a-1) (1 - vu)^(b -1) (k + (1 - k)vu)^(-r) exp(-s u) du
This uses a more stable method for calculating the normalizing constant using R's 'integrate' function rather than the version in Gordy 1998. For calculating Bayes factors that use the 'trCCH' function we recommend using the 'log=TRUE' option to compute log Bayes factors.
Author(s)
Merlise Clyde (clyde@duke.edu)
References
Gordy 1998 Li & Clyde 2018
See Also
Other special functions:
hypergeometric1F1()
,
hypergeometric2F1()
,
phi1()
Examples
# special cases
# trCCH(a, b, r, s=0, v = 1, k) is the same as
# 2F1(a, r, a + b, 1 - 1/k)*beta(a, b)/k^r
k = 10; a = 1.5; b = 2; r = 2;
trCCH(a, b, r, s=0, v = 1, k=k) *k^r/beta(a,b)
hypergeometric2F1(a, r, a + b, 1 - 1/k, log = FALSE)
# trCCH(a,b,0,s,1,1) is the same as
# beta(a, b) 1F1(a, a + b, -s, log=FALSE)
s = 3; r = 0; v = 1; k = 1
beta(a, b)*hypergeometric1F1(a, a+b, -s, log = FALSE)
trCCH(a, b, r, s, v, k)
# Equivalence with the Phi1 function
a = 1.5; b = 3; k = 1.25; s = 400; r = 2; v = 1;
phi1(a, r, a + b, -s, 1 - 1/k, log=FALSE)*(k^-r)*gamma(a)*gamma(b)/gamma(a+b)
trCCH(a,b,r,s,v,k)