Extract model parameters from mkinfit models

This function always returns degradation model parameters as well as error model parameters, in order to avoid working with a fitted model without considering the error structure that was assumed for the fit.

parms(object, ...)

# S3 method for mkinfit
parms(object, transformed = FALSE, ...)

Arguments

object	A fitted model object
...	Not used
transformed	Should the parameters be returned as used internally during the optimisation?

Value

A numeric vector of fitted model parameters

Examples

fit <- mkinfit("SFO", FOCUS_2006_C)
#> Ordinary least squares optimisation
#> Sum of squared residuals at call 1: 2388.077
#> Sum of squared residuals at call 3: 2388.077
#> Sum of squared residuals at call 4: 247.1962
#> Sum of squared residuals at call 7: 200.6791
#> Sum of squared residuals at call 10: 197.7231
#> Sum of squared residuals at call 11: 197.0872
#> Sum of squared residuals at call 14: 196.535
#> Sum of squared residuals at call 15: 196.535
#> Sum of squared residuals at call 16: 196.535
#> Sum of squared residuals at call 17: 196.5334
#> Sum of squared residuals at call 20: 196.5334
#> Sum of squared residuals at call 25: 196.5334
#> Negative log-likelihood at call 31: 26.64668
#> Optimisation successfully terminated.
parms(fit)
#>      parent_0 k_parent_sink         sigma 
#>    82.4921598     0.3060633     4.6730124 
parms(fit, transformed = TRUE)
#>          parent_0 log_k_parent_sink             sigma 
#>         82.492160         -1.183963          4.673012