Lindley {HWEintrinsic} | R Documentation |
Lindley (1988) Two Alleles Data
Description
Four samples of genotype counts previously discussed in previously analyzed by Lindley (1988). For the first three sets, the classical "exact" test rejects the null hypothesis of Hardy-Weinberg equilibrium with significance level below 3.4%, whereas for the last data set the Hardy-Weinberg model is not rejected, its p-value being around 20%.
Usage
data(Lindley)
Format
Four objects of class HWEdata
.
Source
Consonni, G., Gutierrez-Pena, E. and Veronese, P. (2008), "Compatible priors for Bayesian model comparison with an application to the Hardy-Weinberg equilibrium model". Test, Vol. 17, No. 3, 585–605.
References
Consonni, G., Moreno, E., and Venturini, S. (2011). "Testing Hardy-Weinberg equilibrium: an objective Bayesian analysis". Statistics in Medicine, 30, 62–74. https://onlinelibrary.wiley.com/doi/10.1002/sim.4084/abstract Guo, S.W. and Thompson, E.A. (1992), "Performing the Exact Test of Hardy-Weinberg Proportion for Multiple Alleles". Biometrics, 49, 361–372. Lindley D.V. (1988), "Statistical inference concerning Hardy-Weinberg equilibrium". In: Bernardo, J.M., DeGroot, M.H., Lindley, D.V. and Smith, A.F.M. (eds.), "Bayesian statistics 3". Oxford University Press, 307–326.
Examples
## Not run:
# ATTENTION: the following code may take a long time to run! #
data(Lindley)
hwe.ibf.exact <- Vectorize(hwe.ibf, "t")
f <- seq(.05, 1, .05)
n <- sum(dataL1@data.vec, na.rm = TRUE)
# Dataset 1 #
plot(dataL1)
npp.exact <- 1/(1 + hwe.ibf.exact(round(f*n), y = dataL1))
npp.std <- 1/(1 + hwe.bf(dataL1))
plot(f, npp.exact, type="l", lwd = 2, xlab = "f = t/n",
ylab = "Null posterior probability")
abline(h = npp.std, col = gray(.5), lty = "longdash")
# Dataset 2 #
plot(dataL2)
npp.exact <- 1/(1 + hwe.ibf.exact(round(f*n), y = dataL2))
npp.std <- 1/(1 + hwe.bf(dataL2))
plot(f, npp.exact, type="l", lwd = 2, xlab = "f = t/n",
ylab = "Null posterior probability")
abline(h = npp.std, col = gray(.5), lty = "longdash")
# Dataset 3 #
plot(dataL3)
npp.exact <- 1/(1 + hwe.ibf.exact(round(f*n), y = dataL3))
npp.std <- 1/(1 + hwe.bf(dataL3))
plot(f, npp.exact, type="l", lwd = 2, xlab = "f = t/n",
ylab = "Null posterior probability")
abline(h = npp.std, col = gray(.5), lty = "longdash")
# Dataset 4 #
plot(dataL4)
npp.exact <- 1/(1 + hwe.ibf.exact(round(f*n), y = dataL4))
npp.std <- 1/(1 + hwe.bf(dataL4))
plot(f, npp.exact, type="l", lwd = 2, xlab = "f = t/n",
ylab = "Null posterior probability")
abline(h = npp.std, col = gray(.5), lty = "longdash")
## End(Not run)