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.
Arguments
- object
 an object of class 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
- ...
 optional arguments passed to methods like
print.- x
 an object of class
summary.mkinfit.- digits
 Number of digits to use for printing
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
- diffs
 The differential equations used in the model
- use_of_ff
 Was maximum or minimum use made of formation fractions
- bpar
 Optimised and backtransformed parameters
- 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 and fractional eigenvector component g of SFORB systems in 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("SFO", FOCUS_2006_A, quiet = TRUE))
#> mkin version used for fitting:    1.2.10 
#> R version used for fitting:       4.5.0 
#> Date of fit:     Mon May 12 20:26:43 2025 
#> Date of summary: Mon May 12 20:26:43 2025 
#> 
#> Equations:
#> d_parent/dt = - k_parent * parent
#> 
#> Model predictions using solution type analytical 
#> 
#> Fitted using 131 model solutions performed in 0.01 s
#> 
#> Error model: Constant variance 
#> 
#> Error model algorithm: OLS 
#> 
#> Starting values for parameters to be optimised:
#>           value   type
#> parent_0 101.24  state
#> k_parent   0.10 deparm
#> 
#> Starting values for the transformed parameters actually optimised:
#>                   value lower upper
#> parent_0     101.240000  -Inf   Inf
#> log_k_parent  -2.302585  -Inf   Inf
#> 
#> Fixed parameter values:
#> None
#> 
#> Results:
#> 
#>        AIC     BIC    logLik
#>   55.28197 55.5203 -24.64099
#> 
#> Optimised, transformed parameters with symmetric confidence intervals:
#>              Estimate Std. Error  Lower   Upper
#> parent_0      109.200    3.70400 99.630 118.700
#> log_k_parent   -3.291    0.09176 -3.527  -3.055
#> sigma           5.266    1.31600  1.882   8.649
#> 
#> Parameter correlation:
#>               parent_0 log_k_parent     sigma
#> parent_0     1.000e+00    5.428e-01 1.642e-07
#> log_k_parent 5.428e-01    1.000e+00 2.507e-07
#> sigma        1.642e-07    2.507e-07 1.000e+00
#> 
#> 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   29.47 4.218e-07 99.6300 118.70000
#> k_parent   0.03722   10.90 5.650e-05  0.0294   0.04712
#> sigma      5.26600    4.00 5.162e-03  1.8820   8.64900
#> 
#> FOCUS Chi2 error levels in percent:
#>          err.min n.optim df
#> All data   8.385       2  6
#> parent     8.385       2  6
#> 
#> 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