From a77a10ea6c607346778ba0700b3b66ac393101a2 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 27 May 2020 06:06:08 +0200 Subject: Create up to date pkgdown docs in development mode --- docs/dev/reference/logistic.solution.html | 275 ++++++++++++++++++++++++++++++ 1 file changed, 275 insertions(+) create mode 100644 docs/dev/reference/logistic.solution.html (limited to 'docs/dev/reference/logistic.solution.html') diff --git a/docs/dev/reference/logistic.solution.html b/docs/dev/reference/logistic.solution.html new file mode 100644 index 00000000..4804fc73 --- /dev/null +++ b/docs/dev/reference/logistic.solution.html @@ -0,0 +1,275 @@ + + + + + + + + +Logistic kinetics — logistic.solution • mkin + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Function describing exponential decline from a defined starting value, with +an increasing rate constant, supposedly caused by microbial growth

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logistic.solution(t, parent_0, kmax, k0, r)
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Arguments

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t

Time.

parent_0

Starting value for the response variable at time zero.

kmax

Maximum rate constant.

k0

Minimum rate constant effective at time zero.

r

Growth rate of the increase in the rate constant.

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Value

+ +

The value of the response variable at time t.

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Note

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The solution of the logistic model reduces to the +SFO.solution if k0 is equal to kmax.

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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://esdac.jrc.ec.europa.eu/projects/degradation-kinetics +FOCUS (2014) “Generic guidance for Estimating Persistence +and Degradation Kinetics from Environmental Fate Studies on Pesticides in +EU Registration” Report of the FOCUS Work Group on Degradation Kinetics, +Version 1.1, 18 December 2014 +http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics

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See also

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Other parent solutions: +DFOP.solution(), +FOMC.solution(), +HS.solution(), +IORE.solution(), +SFO.solution(), +SFORB.solution()

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Examples

+
+ # Reproduce the plot on page 57 of FOCUS (2014) + plot(function(x) logistic.solution(x, 100, 0.08, 0.0001, 0.2), + from = 0, to = 100, ylim = c(0, 100), + xlab = "Time", ylab = "Residue")
plot(function(x) logistic.solution(x, 100, 0.08, 0.0001, 0.4), + from = 0, to = 100, add = TRUE, lty = 2, col = 2)
plot(function(x) logistic.solution(x, 100, 0.08, 0.0001, 0.8), + from = 0, to = 100, add = TRUE, lty = 3, col = 3)
plot(function(x) logistic.solution(x, 100, 0.08, 0.001, 0.2), + from = 0, to = 100, add = TRUE, lty = 4, col = 4)
plot(function(x) logistic.solution(x, 100, 0.08, 0.08, 0.2), + from = 0, to = 100, add = TRUE, lty = 5, col = 5)
legend("topright", inset = 0.05, + legend = paste0("k0 = ", c(0.0001, 0.0001, 0.0001, 0.001, 0.08), + ", r = ", c(0.2, 0.4, 0.8, 0.2, 0.2)), + lty = 1:5, col = 1:5)
+ # Fit with synthetic data + logistic <- mkinmod(parent = mkinsub("logistic")) + + sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120) + parms_logistic <- c(kmax = 0.08, k0 = 0.0001, r = 0.2) + d_logistic <- mkinpredict(logistic, + parms_logistic, c(parent = 100), + sampling_times) + d_2_1 <- add_err(d_logistic, + sdfunc = function(x) sigma_twocomp(x, 0.5, 0.07), + n = 1, reps = 2, digits = 5, LOD = 0.1, seed = 123456)[[1]] + + m <- mkinfit("logistic", d_2_1, quiet = TRUE) + plot_sep(m)
summary(m)$bpar
#> Estimate se_notrans t value Pr(>t) Lower +#> parent_0 1.057896e+02 1.9023449649 55.610120 3.768361e-16 1.016451e+02 +#> kmax 6.398190e-02 0.0143201029 4.467978 3.841828e-04 3.929235e-02 +#> k0 1.612775e-04 0.0005866813 0.274898 3.940351e-01 5.846685e-08 +#> r 2.263946e-01 0.1718110773 1.317695 1.061044e-01 4.335843e-02 +#> sigma 5.332935e+00 0.9145907310 5.830952 4.036926e-05 3.340213e+00 +#> Upper +#> parent_0 109.9341588 +#> kmax 0.1041853 +#> k0 0.4448750 +#> r 1.1821121 +#> sigma 7.3256566
endpoints(m)$distimes
#> DT50 DT90 DT50_k0 DT50_kmax +#> parent 36.86533 62.41511 4297.854 10.83349
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