pois_mean_GG: Solve Gaussian approximation to Poisson mean problem

In stephenslab/susiF.alpha: Sum of Single Functions

Solve Gaussian approximation to Poisson mean problem

Description

Gaussian prior, Gaussian posterior in Poisson mean problem.

Usage

pois_mean_GG(
  x,
  s = NULL,
  prior_mean = NULL,
  prior_var = NULL,
  optim_method = "L-BFGS-B",
  maxiter = 1000,
  tol = 1e-05
)

Arguments

x	data vector
s	scaling vector
prior_mean	prior mean
prior_var	prior variance
optim_method	optimization method in 'optim' function
maxiter	max number of iterations
tol	tolerance for stopping the updates
w	prior weights

Details

The problem is

x_i\sim Poisson(\exp(\mu_i)),

\mu_i\sim N(\beta,\sigma^2).

Value

a list of

posteriorMean:	posterior mean
posteriorVar:	posterior variance
obj_value:	objective function values
prior_mean:	prior mean
prior_var:	prior variance

@example n=300 x = rpois(n,exp(2*sin(1:n/20))) naive=pois_mean_GG(x) prior_base= pois_mean_GG(x, prior_mean = 2*sin(1:n/20), prior_var=rep(1, length(n))) plot(prior_base$posterior$posteriorMean_latent, col="green", type="l") lines(naive$posterior$posteriorMean_latent) points(2*sin(1:n/20), pch=19)

stephenslab/susiF.alpha documentation built on June 11, 2025, 1:09 p.m.