# Print a causal workflow bundle

`print.causalmixgpd_causal_bundle()` gives a compact structural summary
of the pre-run causal bundle created by
[`build_causal_bundle`](https://arnabaich96.github.io/CausalMixGPD/pkgdown/reference/build_causal_bundle.md).

## Usage

``` r
# S3 method for class 'causalmixgpd_causal_bundle'
print(x, code = FALSE, max_code_lines = 200L, ...)
```

## Arguments

- x:

  A `"causalmixgpd_causal_bundle"` object.

- code:

  Logical; if TRUE, print generated NIMBLE code for each block.

- max_code_lines:

  Integer; maximum number of code lines to print when `code=TRUE`.

- ...:

  Unused.

## Value

The input object (invisibly).

## Details

A causal bundle collects three pre-MCMC building blocks: the optional
propensity-score model for \\e(x) = \Pr(A = 1 \mid X = x)\\, the control
outcome model for \\Y^0\\, and the treated outcome model for \\Y^1\\.
The printed output aligns those blocks side by side so the user can
verify that the treated and control outcome specifications are coherent
before sampling.

No causal estimand is computed at this stage. The bundle only records
the structural assumptions that will later support estimands such as
\\E(Y^1 - Y^0 \mid X = x)\\ or \\Q\_{Y^1}(\tau \mid X = x) -
Q\_{Y^0}(\tau \mid X = x)\\.

## See also

[`summary.causalmixgpd_causal_bundle`](https://arnabaich96.github.io/CausalMixGPD/pkgdown/reference/summary.causalmixgpd_causal_bundle.md),
[`run_mcmc_causal`](https://arnabaich96.github.io/CausalMixGPD/pkgdown/reference/run_mcmc_causal.md),
[`ate`](https://arnabaich96.github.io/CausalMixGPD/pkgdown/reference/ate.md),
[`qte`](https://arnabaich96.github.io/CausalMixGPD/pkgdown/reference/qte.md).

## Examples

``` r
if (FALSE) { # \dontrun{
cb <- build_causal_bundle(y = y, X = X, A = A, backend = "sb", kernel = "normal")
print(cb)
} # }
```