From 082be7baa35d7e8131a70ca8cc061d90e08fa584 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 15 Apr 2020 01:27:02 +0200 Subject: A plot method for nlme.mmkin fits --- docs/reference/nlme.mmkin.html | 301 +++++++++++++++++++++++++++++++++++++++++ 1 file changed, 301 insertions(+) create mode 100644 docs/reference/nlme.mmkin.html (limited to 'docs/reference/nlme.mmkin.html') diff --git a/docs/reference/nlme.mmkin.html b/docs/reference/nlme.mmkin.html new file mode 100644 index 00000000..e1b1ff77 --- /dev/null +++ b/docs/reference/nlme.mmkin.html @@ -0,0 +1,301 @@ + + + + + + + + +Create an nlme model for an mmkin row object — nlme.mmkin • mkin + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+

Create an nlme model for an mmkin row object

+ + +
+ +
+

This functions sets up a nonlinear mixed effects model for an mmkin row +object. An mmkin row object is essentially a list of mkinfit objects that +have been obtained by fitting the same model to a list of datasets.

+
+ + 
# S3 method for mmkin
+nlme(
+  model,
+  data = sys.frame(sys.parent()),
+  fixed,
+  random = fixed,
+  groups,
+  start,
+  correlation = NULL,
+  weights = NULL,
+  subset,
+  method = c("ML", "REML"),
+  na.action = na.fail,
+  naPattern,
+  control = list(),
+  verbose = FALSE
+)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
model

An mmkin row object.

data

Ignored, data are taken from the mmkin model

fixed

Ignored, all degradation parameters fitted in the +mmkin model are used as fixed parameters

random

If not specified, all fixed effects are complemented +with uncorrelated random effects

groups

See the documentation of nlme

start

If not specified, mean values of the fitted degradation +parameters taken from the mmkin object are used

correlation

See the documentation of nlme

weights

passed to nlme

subset

passed to nlme

method

passed to nlme

na.action

passed to nlme

naPattern

passed to nlme

control

passed to nlme

verbose

passed to nlme

+ +

Value

+ +

Upon success, a fitted nlme.mmkin object, which is an nlme object + with additional elements

+

See also

+ +

nlme_function

+ +

Examples

+ 
ds <- lapply(experimental_data_for_UBA_2019[6:10],
+ function(x) subset(x$data[c("name", "time", "value")], name == "parent"))
+f <- mmkin("SFO", ds, quiet = TRUE, cores = 1)
+library(nlme)
+f_nlme <- nlme(f)
+nlme(f, random = parent_0 ~ 1)
#> Nonlinear mixed-effects model fit by maximum likelihood
+#>   Model: value ~ deg_func(name, time, parent_0, log_k_parent_sink) 
+#>   Data: structure(list(ds = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L,  3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L,  4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,  4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,  5L, 5L), .Label = c("1", "2", "3", "4", "5"), class = c("ordered",  "factor")), name = c("parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent"), time = c(0, 0, 3, 3, 6, 6, 10, 10, 20, 20,  34, 34, 55, 55, 90, 90, 112, 112, 132, 132, 0, 0, 3, 3, 7, 7,  14, 14, 30, 30, 60, 60, 90, 90, 120, 120, 180, 180, 0, 0, 1,  1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 0, 0, 1, 1, 3,  3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 91, 91, 120, 120, 0,  0, 8, 8, 14, 14, 21, 21, 41, 41, 63, 63, 91, 91, 120, 120), value = c(97.2,  96.4, 71.1, 69.2, 58.1, 56.6, 44.4, 43.4, 33.3, 29.2, 17.6, 18,  10.5, 9.3, 4.5, 4.7, 3, 3.4, 2.3, 2.7, 93.6, 92.3, 87, 82.2,  74, 73.9, 64.2, 69.5, 54, 54.6, 41.1, 38.4, 32.5, 35.5, 28.1,  29, 26.5, 27.6, 91.9, 90.8, 64.9, 66.2, 43.5, 44.1, 18.3, 18.1,  10.2, 10.8, 4.9, 3.3, 1.6, 1.5, 1.1, 0.9, 99.8, 98.3, 77.1, 77.2,  59, 58.1, 27.4, 29.2, 19.1, 29.6, 10.1, 18.2, 4.5, 9.1, 2.3,  2.9, 2, 1.8, 2, 2.2, 96.1, 94.3, 73.9, 73.9, 69.4, 73.1, 65.6,  65.3, 55.9, 54.4, 47, 49.3, 44.7, 46.7, 42.1, 41.3)), row.names = c(NA,  -90L), class = c("nfnGroupedData", "nfGroupedData", "groupedData",  "data.frame"), formula = value ~ time | ds, FUN = function (x)  max(x, na.rm = TRUE), order.groups = FALSE) 
+#>   Log-likelihood: -394.4901
+#>   Fixed: list(parent_0 ~ 1, log_k_parent_sink ~ 1) 
+#>          parent_0 log_k_parent_sink 
+#>         73.985522         -3.869079 
+#> 
+#> Random effects:
+#>  Formula: parent_0 ~ 1 | ds
+#>         parent_0 Residual
+#> StdDev:  18.6134 18.22029
+#> 
+#> Number of Observations: 90
+#> Number of Groups: 5 
f_nlme <- nlme(f, start = c(parent_0 = 100, log_k_parent_sink = 0.1))
+update(f_nlme, random = parent_0 ~ 1)
#> Nonlinear mixed-effects model fit by maximum likelihood
+#>   Model: value ~ deg_func(name, time, parent_0, log_k_parent_sink) 
+#>   Data: structure(list(ds = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L,  3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L,  4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,  4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,  5L, 5L), .Label = c("1", "2", "3", "4", "5"), class = c("ordered",  "factor")), name = c("parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent", "parent", "parent", "parent", "parent", "parent",  "parent", "parent"), time = c(0, 0, 3, 3, 6, 6, 10, 10, 20, 20,  34, 34, 55, 55, 90, 90, 112, 112, 132, 132, 0, 0, 3, 3, 7, 7,  14, 14, 30, 30, 60, 60, 90, 90, 120, 120, 180, 180, 0, 0, 1,  1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 0, 0, 1, 1, 3,  3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 91, 91, 120, 120, 0,  0, 8, 8, 14, 14, 21, 21, 41, 41, 63, 63, 91, 91, 120, 120), value = c(97.2,  96.4, 71.1, 69.2, 58.1, 56.6, 44.4, 43.4, 33.3, 29.2, 17.6, 18,  10.5, 9.3, 4.5, 4.7, 3, 3.4, 2.3, 2.7, 93.6, 92.3, 87, 82.2,  74, 73.9, 64.2, 69.5, 54, 54.6, 41.1, 38.4, 32.5, 35.5, 28.1,  29, 26.5, 27.6, 91.9, 90.8, 64.9, 66.2, 43.5, 44.1, 18.3, 18.1,  10.2, 10.8, 4.9, 3.3, 1.6, 1.5, 1.1, 0.9, 99.8, 98.3, 77.1, 77.2,  59, 58.1, 27.4, 29.2, 19.1, 29.6, 10.1, 18.2, 4.5, 9.1, 2.3,  2.9, 2, 1.8, 2, 2.2, 96.1, 94.3, 73.9, 73.9, 69.4, 73.1, 65.6,  65.3, 55.9, 54.4, 47, 49.3, 44.7, 46.7, 42.1, 41.3)), row.names = c(NA,  -90L), class = c("nfnGroupedData", "nfGroupedData", "groupedData",  "data.frame"), formula = value ~ time | ds, FUN = function (x)  max(x, na.rm = TRUE), order.groups = FALSE) 
+#>   Log-likelihood: -404.3729
+#>   Fixed: list(parent_0 ~ 1, log_k_parent_sink ~ 1) 
+#>          parent_0 log_k_parent_sink 
+#>         75.933480         -3.555983 
+#> 
+#> Random effects:
+#>  Formula: parent_0 ~ 1 | ds
+#>            parent_0 Residual
+#> StdDev: 0.002416792 21.63027
+#> 
+#> Number of Observations: 90
+#> Number of Groups: 5
+
+ +
+ + + +
+ + + + + + + + -- cgit v1.2.1