From ec1487f0f2cef32d44b0c6ce94a6f1b4f65a79d3 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 6 Oct 2016 08:56:45 +0200 Subject: Remove staticdocs from old location --- inst/web/mkinerrmin.html | 160 ----------------------------------------------- 1 file changed, 160 deletions(-) delete mode 100644 inst/web/mkinerrmin.html (limited to 'inst/web/mkinerrmin.html') diff --git a/inst/web/mkinerrmin.html b/inst/web/mkinerrmin.html deleted file mode 100644 index 25179d52..00000000 --- a/inst/web/mkinerrmin.html +++ /dev/null @@ -1,160 +0,0 @@ - - - - -mkinerrmin. mkin 0.9.44.9000 - - - - - - - - - - - - - - - -
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- mkin 0.9.44.9000 -
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-Calculate the minimum error to assume in order to pass the variance test -

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Usage

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mkinerrmin(fit, alpha = 0.05)
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Arguments

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fit
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- an object of class mkinfit. -
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alpha
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- The confidence level chosen for the chi-squared test. -
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Description

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This function uses optimize in order to iteratively find the -smallest relative error still resulting in passing the chi-squared test -as defined in the FOCUS kinetics report from 2006.

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Value

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- A dataframe with the following components: -
err.min
The relative error, expressed as a fraction.

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n.optim
The number of optimised parameters attributed to the data series.

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df
The number of remaining degrees of freedom for the chi2 error level - calculations. Note that mean values are used for the chi2 statistic and - therefore every time point with observed values in the series only counts - one time.

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The dataframe has one row for the total dataset and one further row for - each observed state variable in the model. -

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Details

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This function is used internally by summary.mkinfit.

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References

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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

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Examples

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SFO_SFO = mkinmod(parent = list(type = "SFO", to = "m1"),
-                  m1 = list(type = "SFO"),
-                  use_of_ff = "max")
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-Successfully compiled differential equation model from auto-generated C code.
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-fit_FOCUS_D = mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
-round(mkinerrmin(fit_FOCUS_D), 4)
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-
         err.min n.optim df
-All data  0.0640       4 15
-parent    0.0646       2  7
-m1        0.0469       2  8
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fit_FOCUS_E = mkinfit(SFO_SFO, FOCUS_2006_E, quiet = TRUE)
-round(mkinerrmin(fit_FOCUS_E), 4)
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         err.min n.optim df
-All data  0.1544       4 13
-parent    0.1659       2  7
-m1        0.1095       2  6
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- - \ No newline at end of file -- cgit v1.2.1