These functions return various objects containing data used in the examples throughout the bayesplot package documentation.
example_mcmc_draws(chains = 4, params = 4)
example_yrep_draws()
example_y_data()
example_x_data()
example_group_data()An integer between 1 and 4 indicating the desired number of chains.
An integer between 1 and 6 indicating the desired number of parameters.
See Details.
Each of these functions returns an object containing data, parameter draws, or
predictions corresponding to a basic linear regression model with data
y (outcome vector) and X (predictor matrix), and parameters
alpha (intercept), beta (coefficient vector), and sigma
(error sd).
example_mcmc_draws()If chains > 1, a 250 (iterations) by chains by
params array or, if chains = 1, a 250 by params
matrix of MCMC draws from the posterior distribution of the parameters in
the linear regression model described above. If params = 1 then only
the draws for alpha are included in the returned object. If
params >= 2 then draws for sigma are also included. And if
params is between 3 and the maximum of 6 then draws
for regression coefficients beta[k] (k in 1:(params-2))
are also included.
example_y_data()A numeric vector with 434 observations of the outcome variable in the
linear regression model.
example_x_data()A numeric vector with 434 observations of one of the predictor
variables in the linear regression model.
example_group_data()A factor variable with 434 observations of a grouping variable with
two levels.
example_yrep_draws()A 500 (draws) by 434 (data points) matrix of draws from the
posterior predictive distribution. Each row represents a full dataset drawn
from the posterior predictive distribution of the outcome y after
fitting the linear regression model mentioned above.
draws <- example_mcmc_draws()
dim(draws)
#> [1] 250 4 4
dimnames(draws)
#> $Iteration
#> NULL
#>
#> $Chain
#> [1] "chain:1" "chain:2" "chain:3" "chain:4"
#>
#> $Parameter
#> [1] "alpha" "sigma" "beta[1]" "beta[2]"
#>
draws <- example_mcmc_draws(1, 2)
dim(draws)
#> [1] 250 2
colnames(draws)
#> [1] "alpha" "sigma"
draws <- example_mcmc_draws(params = 6)
dimnames(draws)[[3]]
#> [1] "alpha" "sigma" "beta[1]" "beta[2]" "beta[3]" "beta[4]"
y <- example_y_data()
x <- example_x_data()
group <- example_group_data()
length(y)
#> [1] 434
length(x)
#> [1] 434
length(group)
#> [1] 434
tail(data.frame(y, x, group), 5)
#> y x group
#> 430 94 84.87741 GroupA
#> 431 76 92.99039 GroupB
#> 432 50 94.85971 GroupA
#> 433 88 96.85662 GroupB
#> 434 70 91.25334 GroupB
yrep <- example_yrep_draws()
dim(yrep) # ncol(yrep) = length(y) = length(x) = length(group)
#> [1] 500 434