Main user-facing function for inverting leaf wax hydrogen isotopes to precipitation isotopes. Automatically selects appropriate model based on available data and returns results in a tidy format.
Usage
predict_d2h_precip(
data = NULL,
d2h_wax = NULL,
longitude = NULL,
latitude = NULL,
d2h_wax_err = NULL,
elevation = NULL,
c4_fraction = NULL,
pft_tree = NULL,
pft_shrub = NULL,
pft_grass = NULL,
model = "auto",
n_draws = NULL,
credible_level = 0.9,
return_draws = FALSE,
progress = TRUE,
verbose = TRUE
)Arguments
- data
Data frame containing measurements, or NULL to use individual vectors
- d2h_wax
Numeric vector of leaf wax d2H values (per mil)
- longitude
Numeric vector of longitudes (decimal degrees)
- latitude
Numeric vector of latitudes (decimal degrees)
- d2h_wax_err
Numeric vector of measurement uncertainties (optional)
- elevation
Numeric vector of elevations in meters (optional)
- c4_fraction
Numeric vector of C4 vegetation fraction 0-1 (optional)
- pft_tree
Numeric vector of tree PFT fraction (optional)
- pft_shrub
Numeric vector of shrub PFT fraction (optional)
- pft_grass
Numeric vector of grass PFT fraction (optional)
- model
Character string specifying model, or "auto" for automatic selection
- n_draws
Integer number of posterior draws (NULL for all)
- credible_level
Numeric credible interval level (default 0.9)
- return_draws
Logical whether to return full posterior draws
- progress
Logical whether to show progress bar for batch processing
- verbose
Logical whether to print status messages
Value
A data frame with predictions (or list if return_draws = TRUE):
- d2h_precip_mean
Mean predicted precipitation d2H
- d2h_precip_median
Median predicted precipitation d2H
- d2h_precip_sd
Standard deviation of the posterior predictive interval
- d2h_precip_lower
Lower bound of the credible interval
- d2h_precip_upper
Upper bound of the credible interval
- prediction_interval_width
Width of the credible interval
- model_used
Name of model used for prediction
The interval is the posterior predictive specified in manuscript supplement Section S4.1, Eq. 7 (analytical uncertainty plus the model's posterior residual SD).
Examples
if (FALSE) { # \dontrun{
# Using data frame input
data(example_data)
results <- predict_d2h_precip(example_data)
# Using individual vectors
results <- predict_d2h_precip(
d2h_wax = c(-150, -140, -130),
longitude = c(-120, -110, -100),
latitude = c(40, 35, 30),
elevation = c(1000, 1500, 500)
)
# Specify model explicitly
results <- predict_d2h_precip(
example_data,
model = "baseline_env_sp"
)
# Get full posterior draws
results <- predict_d2h_precip(
example_data,
return_draws = TRUE
)
} # }