gp_model_fit: A 'stan_fit' object used in the 'ggfan_stan' vignette,...
In ggfan: Summarise a Distribution Through Coloured Intervals

The code needed to recreate the object is included in the examples, as well as in the vignette code chunks.

1	gp_model_fit

A 'stan_fit' object containing samples of the following parameters.

eta_sq: Gaussian process variance parameter
rho_sq: Gaussian process roughness parameter
z: Latent poisson rate
y_gen: Posterior predictive sample of counts 'y'

See the help page for stanfit-class for more details.

## Not run: 
# generate mean and variance for sequence of samples over time
library(rstan)
library(dplyr)
library(magrittr)
library(tidyr)
library(tibble)

library(ggfan)
seed <- 34526
set.seed(seed)

# data 
x <- seq(-5,5,0.1)
N <- length(x)
y <- cbind(rpois(N, exp(sin(x)+2)),rpois(N, exp(sin(x)+2)))

stan_data <- list(N=N, x=x, y=y)


compiled_model <- stan_model(file=file.path(path.package("ggfan"), 
                                            "stan","latent_gp_pois.stan"))
gp_model_fit <- sampling(compiled_model, data=stan_data, iter=3000,thin=6)
#devtools::use_data(gp_model_fit, internal=FALSE)

## End(Not run)