Helper functions to create nlme models from mmkin row objects

+ + +

These functions facilitate setting 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. They are used internally by the nlme.mmkin() method.

+ +

nlme_function(object)
+
+mean_degparms(object, random = FALSE)
+
+nlme_data(object)

+ +

Arguments

+ + + + + + + + + + +

object	An mmkin row object containing several fits of the same model to different datasets
random	Should a list with fixed and random effects be returned?

+ +

Value

+ +

A function that can be used with nlme

If random is FALSE (default), a named vector containing mean values +of the fitted degradation model parameters. If random is TRUE, a list with +fixed and random effects, in the format required by the start argument of +nlme for the case of a single grouping variable ds.

A groupedData object

Examples

sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
+m_SFO <- mkinmod(parent = mkinsub("SFO"))
+d_SFO_1 <- mkinpredict(m_SFO,
+  c(k_parent = 0.1),
+  c(parent = 98), sampling_times)
+d_SFO_1_long <- mkin_wide_to_long(d_SFO_1, time = "time")
+d_SFO_2 <- mkinpredict(m_SFO,
+  c(k_parent = 0.05),
+  c(parent = 102), sampling_times)
+d_SFO_2_long <- mkin_wide_to_long(d_SFO_2, time = "time")
+d_SFO_3 <- mkinpredict(m_SFO,
+  c(k_parent = 0.02),
+  c(parent = 103), sampling_times)
+d_SFO_3_long <- mkin_wide_to_long(d_SFO_3, time = "time")
+
+d1 <- add_err(d_SFO_1, function(value) 3, n = 1)
+d2 <- add_err(d_SFO_2, function(value) 2, n = 1)
+d3 <- add_err(d_SFO_3, function(value) 4, n = 1)
+ds <- c(d1 = d1, d2 = d2, d3 = d3)
+
+f <- mmkin("SFO", ds, cores = 1, quiet = TRUE)
+mean_dp <- mean_degparms(f)
+grouped_data <- nlme_data(f)
+nlme_f <- nlme_function(f)
+# These assignments are necessary for these objects to be
+# visible to nlme and augPred when evaluation is done by
+# pkgdown to generated the html docs.
+assign("nlme_f", nlme_f, globalenv())
+assign("grouped_data", grouped_data, globalenv())
+
+library(nlme)
+m_nlme <- nlme(value ~ nlme_f(name, time, parent_0, log_k_parent_sink),
+  data = grouped_data,
+  fixed = parent_0 + log_k_parent_sink ~ 1,
+  random = pdDiag(parent_0 + log_k_parent_sink ~ 1),
+  start = mean_dp)
+summary(m_nlme)
#> Nonlinear mixed-effects model fit by maximum likelihood
+#>   Model: value ~ nlme_f(name, time, parent_0, log_k_parent_sink) 
+#>  Data: grouped_data 
+#>        AIC      BIC    logLik
+#>   252.7798 262.1358 -121.3899
+#> 
+#> Random effects:
+#>  Formula: list(parent_0 ~ 1, log_k_parent_sink ~ 1)
+#>  Level: ds
+#>  Structure: Diagonal
+#>            parent_0 log_k_parent_sink Residual
+#> StdDev: 0.004139378         0.6800778 2.489396
+#> 
+#> Fixed effects: parent_0 + log_k_parent_sink ~ 1 
+#>                       Value Std.Error DF   t-value p-value
+#> parent_0          101.74884 0.6456057 44 157.60213       0
+#> log_k_parent_sink  -3.05575 0.4015812 44  -7.60929       0
+#>  Correlation: 
+#>                   prnt_0
+#> log_k_parent_sink 0.026 
+#> 
+#> Standardized Within-Group Residuals:
+#>         Min          Q1         Med          Q3         Max 
+#> -2.13168782 -0.68780415  0.08282907  0.85913228  2.95298904 
+#> 
+#> Number of Observations: 48
+#> Number of Groups: 3 
plot(augPred(m_nlme, level = 0:1), layout = c(3, 1))
# augPred does not seem to work on fits with more than one state
+# variable
+
+

+ +

Helper functions to create nlme models from mmkin row objects

Arguments

Value

See also

Examples