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Check quantitative diagnostics from a fitted RtGam model

Source: R/diagnostics.R
check_diagnostics.Rd

Evaluates for convergence, effective degrees of freedom, and residual autocorrelation. If warn_for_diagnostic_failure is set to TRUE, will issue warnings when potential diagnostic issues are detected. The diagnostics are invisibly returned as a list and also stored within the diagnostics element of the provided model object.

Usage

check_diagnostics(fit, warn_for_diagnostic_failure = TRUE)

Arguments

fit

A fitted RtGam model object. This should be the result of calling RtGam::RtGam() with appropriate data.

warn_for_diagnostic_failure

A logical value indicating whether to issue warnings if diagnostic checks suggest potential issues with the model fit. Defaults to TRUE, meaning that warnings will be issued by default.

Value

Invisibly returns a list containing diagnostic results:

  • model_converged: Logical indicating if the model has converged.

  • k_prime: The maximum available number of degrees of freedom that could be used in the GAM fit.

  • k_edf: Estimated degrees of freedom actually used by the smooth terms in the model.

  • k_index: The ratio of the residual variance of differenced near-neighbor residuals to the overall residual variance. This should be near 1 or above.

  • k_p_value: P-value for testing if k' is adequate for modeling the data.

  • k_to_edf_ratio: Ratio of k' to effective degrees of freedom of the smooth terms. k' should be well below the available edf.

  • residual_autocorrelation: Autocorrelation coefficients for residuals up to lag 7 or one-tenth of series length, whichever is smaller.

See also

mgcv::k.check for a description of the diagnostic tests, mgcv::choose.k for a description of discussion of choosing the basis dimension, and Wood, Simon N. Generalized additive models: an introduction with R. chapman and hall/CRC, 2017. for a derivation of the metrics.

Examples

withr::with_seed(12345, {
  cases <- rpois(20, 10)
})
reference_date <- seq.Date(
  from = as.Date("2023-01-01"),
  length.out = 20,
  by = "day"
)
fit <- RtGam::RtGam(cases, reference_date)
check_diagnostics(fit)