hypergeometric2F1: Gaussian hypergeometric2F1 function
In BAS: Bayesian Variable Selection and Model Averaging using Bayesian Adaptive Sampling

hypergeometric2F1

R Documentation

Gaussian hypergeometric2F1 function

Description

Compute the Gaussian Hypergeometric2F1 function: 2F1(a,b,c,z) = Gamma(b-c) Int_0^1 t^(b-1) (1 - t)^(c -b -1) (1 - t z)^(-a) dt

Usage

hypergeometric2F1(a, b, c, z, method = "Cephes", log = TRUE)

Arguments

`a`	arbitrary
`b`	Must be greater 0
`c`	Must be greater than b if \|z\| < 1, and c > b + a if z = 1
`z`	\|z\| <= 1
`method`	The default is to use the Cephes library routine. This sometimes is unstable for large a or z near one returning Inf or negative values. In this case, try method="Laplace", which use a Laplace approximation for tau = exp(t/(1-t)).
`log`	if TRUE, return log(2F1)

Details

The default is to use the routine hyp2f1.c from the Cephes library. If that return a negative value or Inf, one should try method="Laplace" which is based on the Laplace approximation as described in Liang et al JASA 2008. This is used in the hyper-g prior to calculate marginal likelihoods.

Value

if log=T returns the log of the 2F1 function; otherwise the 2F1 function.

Author(s)

Merlise Clyde (clyde@duke.edu)

References

Cephes library hyp2f1.c

Liang, F., Paulo, R., Molina, G., Clyde, M. and Berger, J.O. (2005) Mixtures of g-priors for Bayesian Variable Selection. Journal of the American Statistical Association. 103:410-423.
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