From 8bdb4cd437a9d4663e542f95869e8692aa38dadb Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 7 May 2020 08:59:29 +0200 Subject: Static documentation rebuilt by pkgdown --- docs/reference/logistic.solution.html | 125 ++++++++++++++++++++++------------ 1 file changed, 80 insertions(+), 45 deletions(-) (limited to 'docs/reference/logistic.solution.html') diff --git a/docs/reference/logistic.solution.html b/docs/reference/logistic.solution.html index b2f24d45..3e87b90d 100644 --- a/docs/reference/logistic.solution.html +++ b/docs/reference/logistic.solution.html @@ -10,23 +10,27 @@ - + - + - + + + + + - - + + - + - - + + @@ -37,8 +41,9 @@ - @@ -56,7 +61,7 @@ an increasing rate constant, supposedly caused by microbial growth" /> - +
@@ -114,7 +119,12 @@ an increasing rate constant, supposedly caused by microbial growth" />
@@ -129,16 +139,20 @@ an increasing rate constant, supposedly caused by microbial growth" />

Logistic kinetics

- + Source: R/logistic.solution.R, R/parent_solutions.R

Function describing exponential decline from a defined starting value, with +an increasing rate constant, supposedly caused by microbial growth

+

Function describing exponential decline from a defined starting value, with an increasing rate constant, supposedly caused by microbial growth

- 
logistic.solution(t, parent.0, kmax, k0, r)
+ 
logistic.solution(t, parent_0, kmax, k0, r)
+
+logistic.solution(t, parent_0, kmax, k0, r)

Arguments

@@ -148,7 +162,7 @@ an increasing rate constant, supposedly caused by microbial growth

- + @@ -163,6 +177,10 @@ an increasing rate constant, supposedly caused by microbial growth

+ + + +

Time.
parent.0parent_0

Starting value for the response variable at time zero.
r

Growth rate of the increase in the rate constant.
parent.0

Starting value for the response variable at time zero.

Value

@@ -171,6 +189,8 @@ an increasing rate constant, supposedly caused by microbial growth

Note

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

+

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

References

@@ -179,16 +199,25 @@ an increasing rate constant, supposedly caused by microbial growth

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

+

See also

+ +

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

Examples


   # Reproduce the plot on page 57 of FOCUS (2014)
-  plot(function(x) logistic.solution(x, 100, 0.08, 0.0001, 0.2),
+  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),
+       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)),
@@ -205,32 +234,38 @@ an increasing rate constant, supposedly caused by microbial growth

     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

+  m <- mkinfit("logistic", d_2_1, quiet = TRUE)
#> Error in (function (t, parent_0, kmax, k0, r) {    parent = parent_0 * (kmax/(kmax - k0 + k0 * exp(r * t)))^(kmax/r)})(t = c(0, 1, 1.21212121212121, 2.42424242424242, 3, 3.63636363636364, 4.84848484848485, 6.06060606060606, 7, 7.27272727272727, 8.48484848484848, 9.6969696969697, 10.9090909090909, 12.1212121212121, 13.3333333333333, 14, 14.5454545454545, 15.7575757575758, 16.969696969697, 18.1818181818182, 19.3939393939394, 20.6060606060606, 21.8181818181818, 23.030303030303, 24.2424242424242, 25.4545454545455, 26.6666666666667, 27.8787878787879, 28, 29.0909090909091, 30.3030303030303, 31.5151515151515, 32.7272727272727, 33.9393939393939, 35.1515151515152, 36.3636363636364, 37.5757575757576, 38.7878787878788, 40, 41.2121212121212, 42.4242424242424, 43.6363636363636, 44.8484848484849, 46.0606060606061, 47.2727272727273, 48.4848484848485, 49.6969696969697, 50.9090909090909, 52.1212121212121, 53.3333333333333, 54.5454545454545, 55.7575757575758, 56.969696969697, 58.1818181818182, 59.3939393939394, 60, 60.6060606060606, 61.8181818181818, 63.030303030303, 64.2424242424242, 65.4545454545455, 66.6666666666667, 67.8787878787879, 69.0909090909091, 70.3030303030303, 71.5151515151515, 72.7272727272727, 73.9393939393939, 75.1515151515152, 76.3636363636364, 77.5757575757576, 78.7878787878788, 80, 81.2121212121212, 82.4242424242424, 83.6363636363636, 84.8484848484848, 86.0606060606061, 87.2727272727273, 88.4848484848485, 89.6969696969697, 90, 90.9090909090909, 92.1212121212121, 93.3333333333333, 94.5454545454545, 95.7575757575758, 96.969696969697, 98.1818181818182, 99.3939393939394, 100.606060606061, 101.818181818182, 103.030303030303, 104.242424242424, 105.454545454545, 106.666666666667, 107.878787878788, 109.090909090909, 110.30303030303, 111.515151515152, 112.727272727273, 113.939393939394, 115.151515151515, 116.363636363636, 117.575757575758, 118.787878787879, 120), parent.0 = c(parent = 101.95687), kmax = 0.1,     k0 = 1e-04, r = 0.2): unbenutztes Argument (parent.0 = 101.95687)
#> Timing stopped at: 0.001 0 0.001
  plot_sep(m)
#> Error in identical(fit$err_mod, "const"): Objekt 'm' nicht gefunden
  summary(m)$bpar
#> Error in summary(m): Objekt 'm' nicht gefunden
  endpoints(m)$distimes
#> Error in endpoints(m): Objekt 'm' nicht gefunden

+
+  # 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)
#> Error in (function (t, parent_0, kmax, k0, r) {    parent = parent_0 * (kmax/(kmax - k0 + k0 * exp(r * t)))^(kmax/r)})(t = c(0, 1, 1.21212121212121, 2.42424242424242, 3, 3.63636363636364, 4.84848484848485, 6.06060606060606, 7, 7.27272727272727, 8.48484848484848, 9.6969696969697, 10.9090909090909, 12.1212121212121, 13.3333333333333, 14, 14.5454545454545, 15.7575757575758, 16.969696969697, 18.1818181818182, 19.3939393939394, 20.6060606060606, 21.8181818181818, 23.030303030303, 24.2424242424242, 25.4545454545455, 26.6666666666667, 27.8787878787879, 28, 29.0909090909091, 30.3030303030303, 31.5151515151515, 32.7272727272727, 33.9393939393939, 35.1515151515152, 36.3636363636364, 37.5757575757576, 38.7878787878788, 40, 41.2121212121212, 42.4242424242424, 43.6363636363636, 44.8484848484849, 46.0606060606061, 47.2727272727273, 48.4848484848485, 49.6969696969697, 50.9090909090909, 52.1212121212121, 53.3333333333333, 54.5454545454545, 55.7575757575758, 56.969696969697, 58.1818181818182, 59.3939393939394, 60, 60.6060606060606, 61.8181818181818, 63.030303030303, 64.2424242424242, 65.4545454545455, 66.6666666666667, 67.8787878787879, 69.0909090909091, 70.3030303030303, 71.5151515151515, 72.7272727272727, 73.9393939393939, 75.1515151515152, 76.3636363636364, 77.5757575757576, 78.7878787878788, 80, 81.2121212121212, 82.4242424242424, 83.6363636363636, 84.8484848484848, 86.0606060606061, 87.2727272727273, 88.4848484848485, 89.6969696969697, 90, 90.9090909090909, 92.1212121212121, 93.3333333333333, 94.5454545454545, 95.7575757575758, 96.969696969697, 98.1818181818182, 99.3939393939394, 100.606060606061, 101.818181818182, 103.030303030303, 104.242424242424, 105.454545454545, 106.666666666667, 107.878787878788, 109.090909090909, 110.30303030303, 111.515151515152, 112.727272727273, 113.939393939394, 115.151515151515, 116.363636363636, 117.575757575758, 118.787878787879, 120), parent.0 = c(parent = 101.95687), kmax = 0.1,     k0 = 1e-04, r = 0.2): unbenutztes Argument (parent.0 = 101.95687)
#> Timing stopped at: 0 0 0
  plot_sep(m)
#> Error in identical(fit$err_mod, "const"): Objekt 'm' nicht gefunden
  summary(m)$bpar
#> Error in summary(m): Objekt 'm' nicht gefunden
  endpoints(m)$distimes
#> Error in endpoints(m): Objekt 'm' nicht gefunden
- @@ -241,7 +276,7 @@ an increasing rate constant, supposedly caused by microbial growth

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 1.5.1.

-- cgit v1.2.1