gp_model_fit | R Documentation |
stan_fit
object used in the ggfan_stan
vignette, containing posterior samples
from a latent gaussian process model. This is provided as data to avoid
having to conduct computationally expensive sampling when producing the vignettes.The code needed to recreate the object is included in the examples, as well as in the vignette code chunks.
gp_model_fit
A 'stan_fit' object containing samples of the following parameters.
Gaussian process variance parameter
Gaussian process roughness parameter
Latent poisson rate
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)
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