Plot method for ratiod_fit — plot.ratiod

Creates diagnostic plots for ratio model fits including trace plots and optional density plots. Works with all backends (HMC, PG, Laplace).

Usage

# S3 method for class 'ratiod_fit'
plot(x, pars = NULL, type = c("trace", "dens", "both"), n_col = NULL, ...)

Arguments

x: A ratiod_fit object
pars: Character vector of parameter names to plot. If NULL (default), plots main parameters (fixed effects, variance components).
type: Type of plot: "trace" (default), "dens" (density), or "both".
n_col: Number of columns in the plot grid (default: auto).
...: Additional arguments (currently ignored).

Value

Invisibly returns the plot object (base graphics or ggplot2).

Examples

# Create simple dataset
set.seed(456)
df <- data.frame(
  count = rpois(40, 8),
  effort = rgamma(40, 2, 0.5),
  depth = rnorm(40),
  site = factor(sample(1:4, 40, replace = TRUE))
)

# \donttest{
fit <- tratio(
  count | effort ~ depth + (1|site),
  data = df,
  family = ratiod_poisson_gamma(),
  control = list(iter = 200, warmup = 100, chains = 2)
)
#> Inference: Exact (Tier 1)
#>   Backend: hmc
#>   Reason: default (full MCMC)
#> Fitting ratio model...
#>   Family: poisson_gamma
#>   Observations: 40
#>   Iterations: 200 (warmup: 100)
#> Running NUTS sampler...
#>   Parameters: 10
#>   Iterations: 200 (warmup: 100)
#>   Chains: 2 (cores: 2)
plot(fit)

plot(fit, pars = "beta_num", type = "both")

# }