Lists model equations, initial parameter values, optimised parameters with some uncertainty statistics, the chi2 error levels calculated according to FOCUS guidance (2006) as defined therein, formation fractions, DT50 values and optionally the data, consisting of observed, predicted and residual values.

# S3 method for mkinfit
summary(object, data = TRUE, distimes = TRUE, alpha = 0.05, ...)
# S3 method for summary.mkinfit
print(x, digits = max(3, getOption("digits") - 3), ...)

Arguments

object

an object of class mkinfit.

x

an object of class summary.mkinfit.

data

logical, indicating whether the data should be included in the summary.

distimes

logical, indicating whether DT50 and DT90 values should be included.

alpha

error level for confidence interval estimation from t distribution

digits

Number of digits to use for printing

optional arguments passed to methods like print.

Value

The summary function returns a list with components, among others

version, Rversion

The mkin and R versions used

date.fit, date.summary

The dates where the fit and the summary were produced

use_of_ff

Was maximum or minimum use made of formation fractions

residuals, residualVariance, sigma, modVariance, df

As in summary.modFit

cov.unscaled, cov.scaled, info, niter, stopmess, par

As in summary.modFit

bpar

Optimised and backtransformed parameters

diffs

The differential equations used in the model

data

The data (see Description above).

start

The starting values and bounds, if applicable, for optimised parameters.

fixed

The values of fixed parameters.

errmin

The chi2 error levels for each observed variable.

bparms.ode

All backtransformed ODE parameters, for use as starting parameters for related models.

errparms

Error model parameters.

ff

The estimated formation fractions derived from the fitted model.

distimes

The DT50 and DT90 values for each observed variable.

SFORB

If applicable, eigenvalues of SFORB components of the model.

The print method is called for its side effect, i.e. printing the summary.

References

FOCUS (2006) “Guidance Document on Estimating Persistence and Degradation Kinetics from Environmental Fate Studies on Pesticides in EU Registration” Report of the FOCUS Work Group on Degradation Kinetics, EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics

Examples

summary(mkinfit(mkinmod(parent = mkinsub("SFO")), FOCUS_2006_A, quiet = TRUE))
#> Warning: Could not calculate correlation; no covariance matrix
#> mkin version used for fitting: 0.9.49.4 #> R version used for fitting: 3.6.0 #> Date of fit: Tue May 7 08:09:03 2019 #> Date of summary: Tue May 7 08:09:03 2019 #> #> Equations: #> d_parent/dt = - k_parent_sink * parent #> #> Model predictions using solution type analytical #> #> Fitted using 39 model solutions performed in 0.08 s #> #> Error model: #> Constant variance #> #> Starting values for parameters to be optimised: #> value type #> parent_0 101.240000 state #> k_parent_sink 0.100000 deparm #> sigma 5.265546 error #> #> Starting values for the transformed parameters actually optimised: #> value lower upper #> parent_0 101.240000 -Inf Inf #> log_k_parent_sink -2.302585 -Inf Inf #> sigma 5.265546 0 Inf #> #> Fixed parameter values: #> None #> #> Optimised, transformed parameters with symmetric confidence intervals: #> Estimate Std. Error Lower Upper #> parent_0 109.200 NA NA NA #> log_k_parent_sink -3.291 NA NA NA #> sigma 5.266 NA NA NA #> #> Parameter correlation: #> No covariance matrix #> Backtransformed parameters: #> Confidence intervals for internally transformed parameters are asymmetric. #> t-test (unrealistically) based on the assumption of normal distribution #> for estimators of untransformed parameters. #> Estimate t value Pr(>t) Lower Upper #> parent_0 109.20000 NA NA NA NA #> k_parent_sink 0.03722 NA NA NA NA #> sigma 5.26600 NA NA NA NA #> #> FOCUS Chi2 error levels in percent: #> err.min n.optim df #> All data 8.385 2 6 #> parent 8.385 2 6 #> #> Resulting formation fractions: #> ff #> parent_sink 1 #> #> Estimated disappearance times: #> DT50 DT90 #> parent 18.62 61.87 #> #> Data: #> time variable observed predicted residual #> 0 parent 101.24 109.153 -7.9132 #> 3 parent 99.27 97.622 1.6484 #> 7 parent 90.11 84.119 5.9913 #> 14 parent 72.19 64.826 7.3641 #> 30 parent 29.71 35.738 -6.0283 #> 62 parent 5.98 10.862 -4.8818 #> 90 parent 1.54 3.831 -2.2911 #> 118 parent 0.39 1.351 -0.9613