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The function fits the SFO, IORE and DFOP models using mmkin and returns an object of class nafta that has methods for printing and plotting.

Print nafta objects. The results for the three models are printed in the order of increasing model complexity, i.e. SFO, then IORE, and finally DFOP.

Usage

nafta(ds, title = NA, quiet = FALSE, ...)

# S3 method for nafta
print(x, quiet = TRUE, digits = 3, ...)

Source

NAFTA (2011) Guidance for evaluating and calculating degradation kinetics in environmental media. NAFTA Technical Working Group on Pesticides https://www.epa.gov/pesticide-science-and-assessing-pesticide-risks/guidance-evaluating-and-calculating-degradation accessed 2019-02-22

US EPA (2015) Standard Operating Procedure for Using the NAFTA Guidance to Calculate Representative Half-life Values and Characterizing Pesticide Degradation https://www.epa.gov/pesticide-science-and-assessing-pesticide-risks/standard-operating-procedure-using-nafta-guidance

Arguments

ds

A dataframe that must contain one variable called "time" with the time values specified by the time argument, one column called "name" with the grouping of the observed values, and finally one column of observed values called "value".

title

Optional title of the dataset

quiet

Should the evaluation text be shown?

...

Further arguments passed to mmkin (not for the printing method).

x

An nafta object.

digits

Number of digits to be used for printing parameters and dissipation times.

Value

An list of class nafta. The list element named "mmkin" is the mmkin object containing the fits of the three models. The list element named "title" contains the title of the dataset used. The list element "data" contains the dataset used in the fits.

Author

Johannes Ranke

Examples


  nafta_evaluation <- nafta(NAFTA_SOP_Appendix_D, cores = 1)
#> The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
#> The representative half-life of the IORE model is longer than the one corresponding
#> to the terminal degradation rate found with the DFOP model.
#> The representative half-life obtained from the DFOP model may be used
  print(nafta_evaluation)
#> Sums of squares:
#>       SFO      IORE      DFOP 
#> 1378.6832  615.7730  517.8836 
#> 
#> Critical sum of squares for checking the SFO model:
#> [1] 717.4598
#> 
#> Parameters:
#> $SFO
#>          Estimate   Pr(>t)    Lower   Upper
#> parent_0  83.7558 1.80e-14 77.18268 90.3288
#> k_parent   0.0017 7.43e-05  0.00112  0.0026
#> sigma      8.7518 1.22e-05  5.64278 11.8608
#> 
#> $IORE
#>                Estimate Pr(>t)    Lower    Upper
#> parent_0       9.69e+01     NA 8.88e+01 1.05e+02
#> k__iore_parent 8.40e-14     NA 1.79e-18 3.94e-09
#> N_parent       6.68e+00     NA 4.19e+00 9.17e+00
#> sigma          5.85e+00     NA 3.76e+00 7.94e+00
#> 
#> $DFOP
#>          Estimate   Pr(>t)    Lower    Upper
#> parent_0 9.76e+01 1.94e-13 9.02e+01 1.05e+02
#> k1       4.24e-02 5.92e-03 2.03e-02 8.88e-02
#> k2       8.24e-04 6.48e-03 3.89e-04 1.75e-03
#> g        2.88e-01 2.47e-05 1.95e-01 4.03e-01
#> sigma    5.36e+00 2.22e-05 3.43e+00 7.30e+00
#> 
#> 
#> DTx values:
#>      DT50    DT90 DT50_rep
#> SFO   407    1350      407
#> IORE  541 5190000  1560000
#> DFOP  429    2380      841
#> 
#> Representative half-life:
#> [1] 841.41
  plot(nafta_evaluation)