Description Usage Arguments Details Value Author(s) References Examples
A selection of kinetic models as defined in the FOCUS kinetics report from 2006 are fitted to a given dataframe of chemical degradation data.
1 2 3 4 5 6 | kinfit(kindata, kinmodels = c("SFO"), parent.0.user = NA, parent.0.fixed = FALSE,
start.SFO = list(parent.0 = NA, k = NA),
start.FOMC = list(parent.0 = NA, alpha = NA, beta = NA),
start.DFOP = list(parent.0 = NA, k1 = NA, k2 = NA, g = NA),
start.HS = list(parent.0 = NA, k1 = NA, k2 = NA, tb = NA),
algorithm = "default")
|
kindata |
A data frame containing a time variable named |
kinmodels |
An array of character strings which are names of the models to be fit.
Possible names are |
parent.0.user |
The user can give a starting estimate for parent.0 here, overriding other potential sources for starting values as specified below. |
parent.0.fixed |
If TRUE, the initial value for the observed value will be fixed to the
value specified by |
start.SFO |
A list of starting parameters for fitting the |
start.FOMC |
A list of starting parameters for fitting the |
start.DFOP |
A list of starting parameters for fitting the |
start.HS |
A list of starting parameters for fitting the |
algorithm |
The algorithm to use for the calls to |
Per default all starting parameters are NA
and the function tries to
find suitable starting parameters on its own.
A list of models of class nls
representing the models that were
fitted successfully.
Johannes Ranke
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://focus.jrc.ec.europa.eu/dk
1 2 3 4 | data(FOCUS_2006_A)
(kinfits <- kinfit(FOCUS_2006_A))
data(FOCUS_2006_B)
(kinfits <- kinfit(FOCUS_2006_B, kinmodels=c("SFO","FOMC")))
|
$SFO
Nonlinear regression model
model: parent ~ SFO(t, parent.0, k)
data: kindata
parent.0 k
109.15313 0.03722
residual sum-of-squares: 221.8
Number of iterations to convergence: 7
Achieved convergence tolerance: 6.359e-06
$SFO
Nonlinear regression model
model: parent ~ SFO(t, parent.0, k)
data: kindata
parent.0 k
99.17405 0.07816
residual sum-of-squares: 30.66
Number of iterations to convergence: 4
Achieved convergence tolerance: 8.531e-06
$FOMC
Nonlinear regression model
model: parent ~ FOMC(t, parent.0, alpha, beta)
data: kindata
parent.0 alpha beta
99.67 12.81 156.11
residual sum-of-squares: 28.58
Number of iterations to convergence: 8
Achieved convergence tolerance: 4.184e-06
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