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()

## Arguments

chains 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.

## 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.

## Examples

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
#> [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