fun_integ: Calculate the integrand for the marginal distribution of X...
In tamustatsy/bcdd: Bayesian constrained density deconvolution

Description Usage Arguments Value Examples

The (posterior) marginal distribution of X equals the integral of the conditional distribution of X given theta, uniform over [-theta, theta], weighted by the (posterior) distribution of theta, a mixture of Gammas. The function fun_integ explicitly computes the integrand as a function of theta.

1	fun_integ(x, pi, shape, rate)

`x`	a number (vector) specifies the value of the domain argument.
`pi`	a vector containing the component probabilities of the Gammas
`shape,`	rate numeric vectors corresponding to shape and rate parameters of Gammas

The (posterior) marginal distribution of X (over theta) at the input parameter x.

pi <- c(0.2,0.5,0.3)
shape <- c(2.3,3.3,4.3) 
rate <- c(1.5,2.5,3.5)
theta <- 0.1 
fun_integ(theta, pi, shape, rate)
theta <- c(0.1,0.5,3)
fun_integ(theta, pi, shape, rate)