Joint Bayesian inversion of a multi-sample record

Each row has its own latent precipitation-isotope value and proper prior, while all rows share and jointly reweight the paired calibration draws.

Usage

bayesian_record_inverse(
  y,
  intercept,
  slope,
  residual_sd,
  analytical_sd = 0,
  prior,
  credible_level = 0.9,
  grid_size = 2001L,
  integration_tolerance = 0.001,
  tail_mass_tolerance = 1e-08,
  max_refinements = 4L,
  n_samples,
  seed
)

Arguments

y

Numeric vector of observed response values.

intercept, slope

Matrices with calibration draws in rows and observations in columns.

residual_sd

Positive vector with one value per calibration draw.

analytical_sd

Non-negative scalar or one value per observation.

prior

A leafwax_d2h_prior, applied to every observation, or a list containing one such prior per observation.

credible_level

Probability in the central credible interval.

grid_size

Odd number of grid points used for numerical integration.

integration_tolerance

Maximum permitted change in reported summaries between nested numerical grids, in precipitation-isotope units.

tail_mass_tolerance

Maximum permitted posterior mass in either outer grid cell for an unbounded prior.

max_refinements

Maximum domain-expansion attempts.

n_samples

Number of joint posterior samples. Set to zero for a deterministic summary without samples.

seed

Required integer seed when n_samples is positive.

Value

A leafwax_inverse object with row summaries, diagnostics, marginal grids, joint samples, and sampled calibration-draw identifiers.