stanfit-class: Class `stanfit`: fitted Stan model

Description

The output derived from fitting a Stan model, including the samples, as returned by the top-level function stan or the lower-level sampling method sampling defined on class stanmodel. print and plot and other methods are provided for the summaries of the fitted results. Access methods allow the underlying data making up a fit to be retrieved. There are three modes; sampling mode, test gradient mode, error mode (no samples included). The model's functions for computing the log probability density lp__ and the gradient are also exposed for a stanfit object.

Usage

As.mcmc.list(object, pars, include = TRUE, ...)

Arguments

object

object of class "stanfit"

pars

optional character vector of parameters to include

include

logical scalar indicating whether to include (the default) or exclude theh parameters named in pars

...

unused

Objects from the Class

Objects should be created by either calling function stan or sampling method in S4 class stan_model.

References

The Stan Development Team Stan Modeling Language User's Guide and Reference Manual. http://mc-stan.org.

Examples

Run this code

showClass("stanfit")
ecode <- '
  parameters {
    real<lower=0> y[2];
  } 
  model {
    y ~ exponential(1);
  }
'
fit <- stan(model_code = ecode, iter = 10, chains = 1)
fit2 <- stan(fit = fit)
print(fit2)
plot(fit2)
traceplot(fit2)
ainfo <- get_adaptation_info(fit2)
cat(ainfo[[1]])
seed <- get_seed(fit2)
sp <- get_sampler_params(fit2)
sp2 <- get_sampler_params(fit2, inc_warmup = FALSE)
head(sp[[1]])

lp <- log_prob(fit, c(1, 2))
grad <- grad_log_prob(fit, c(1, 2))
lp2 <- attr(grad, "log_prob") # should be the same as "lp"

# get the number of parameters on the unconstrained space
n <- get_num_upars(fit)

# parameters on the positive real line (constrained space) 
y1 <- list(y = rep(1, 2)) 

uy <- unconstrain_pars(fit, y1) 
## uy should be c(0, 0) since here the log transformation is used
y1star <- constrain_pars(fit, uy)

print(y1)
print(y1star) # y1start should equal to y1

# Create a stanfit object from reading CSV files of samples (saved in rstan
# package) generated by funtion stan for demonstration purpose from model as follows. 
# 
excode <- '
  transformed data {
    real y[20];
    y[1] <- 0.5796;  y[2]  <- 0.2276;   y[3] <- -0.2959; 
    y[4] <- -0.3742; y[5]  <- 0.3885;   y[6] <- -2.1585;
    y[7] <- 0.7111;  y[8]  <- 1.4424;   y[9] <- 2.5430; 
    y[10] <- 0.3746; y[11] <- 0.4773;   y[12] <- 0.1803; 
    y[13] <- 0.5215; y[14] <- -1.6044;  y[15] <- -0.6703; 
    y[16] <- 0.9459; y[17] <- -0.382;   y[18] <- 0.7619;
    y[19] <- 0.1006; y[20] <- -1.7461;
  }
  parameters {
    real mu;
    real<lower=0, upper=10> sigma;
    vector[2] z[3];
    real<lower=0> alpha;
  } 
  model {
    y ~ normal(mu, sigma);
    for (i in 1:3) 
      z[i] ~ normal(0, 1);
    alpha ~ exponential(2);
  } 
'

# exfit <- stan(model_code = excode, save_dso = FALSE, iter = 200, 
#               sample_file = "rstan_doc_ex.csv")
# 

exfit <- read_stan_csv(dir(system.file('misc', package = 'rstan'),
                       pattern='rstan_doc_ex_[[:digit:]].csv',
                       full.names = TRUE))

print(exfit)
plot(exfit)

adaptinfo <- get_adaptation_info(exfit)
seed <- get_seed(exfit)
sp <- get_sampler_params(exfit)
ml <- As.mcmc.list(exfit)