rstan (version 2.9.0-3)

traceplot-methods: traceplot: draw the traces of the sample

Description

Draw the traceplot corresponding to one or more Markov chains, providing a visual way to inspect sampling behavior and assess mixing across chains and convergence.

Usage

## S3 method for class 'stanfit':
traceplot(object, pars, include = TRUE, unconstrain = FALSE, 
          inc_warmup = FALSE, nrow = NULL, ncol = NULL, ...)

Arguments

object

An instance of class stanfit.

pars

A character vector of parameter names. Defaults to all parameters or the first 10 parameters (if there are more than 10).

include

Should the parameters given by the pars argument be included (the default) or excluded from the plot? Only relevant if pars is not missing.

inc_warmup

TRUE or FALSE, indicating whether the warmup sample are included in the trace plot; defaults to FALSE.

unconstrain

Should parameters be plotted on the unconstrained space? Defaults to FALSE.

nrow,ncol

Passed to facet_wrap.

...

Optional arguments to pass to geom_path (e.g. size, linetype, alpha, etc.).

Value

• A ggplot object that can be further customized using the ggplot2 package.

See Also

List of RStan plotting functions, Plot options

Examples

library(rstan) 
fit <- stan(model_code = "parameters {real y;} model {y ~ normal(0,1);}") 
traceplot(fit) 
traceplot(fit, inc_warmup = TRUE, nrow = 2)
traceplot(fit) + coord_cartesian(xlim = c(1500,1600))


# 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)
traceplot(exfit)
traceplot(exfit, size = 0.25)
traceplot(exfit, pars = "sigma", inc_warmup = TRUE)

trace <- traceplot(exfit, pars = c("z[1,1]", "z[3,1]"))
trace + scale_color_discrete() + theme(legend.position = "top")