transform_odeparms {mkin} | R Documentation |
The transformations are intended to map parameters that should only take on
restricted values to the full scale of real numbers. For kinetic rate
constants and other paramters that can only take on positive values, a
simple log transformation is used. For compositional parameters, such as the
formations fractions that should always sum up to 1 and can not be negative,
the ilr
transformation is used.
transform_odeparms( parms, mkinmod, transform_rates = TRUE, transform_fractions = TRUE ) backtransform_odeparms( transparms, mkinmod, transform_rates = TRUE, transform_fractions = TRUE )
parms |
Parameters of kinetic models as used in the differential equations. |
mkinmod |
The kinetic model of class |
transform_rates |
Boolean specifying if kinetic rate constants should be transformed in the model specification used in the fitting for better compliance with the assumption of normal distribution of the estimator. If TRUE, also alpha and beta parameters of the FOMC model are log-transformed, as well as k1 and k2 rate constants for the DFOP and HS models and the break point tb of the HS model. |
transform_fractions |
Boolean specifying if formation fractions
constants should be transformed in the model specification used in the
fitting for better compliance with the assumption of normal distribution
of the estimator. The default (TRUE) is to do transformations. The g
parameter of the DFOP and HS models are also transformed, as they can also
be seen as compositional data. The transformation used for these
transformations is the |
transparms |
Transformed parameters of kinetic models as used in the fitting procedure. |
The transformation of sets of formation fractions is fragile, as it supposes
the same ordering of the components in forward and backward transformation.
This is no problem for the internal use in mkinfit
.
A vector of transformed or backtransformed parameters with the same names as the original parameters.
backtransform_odeparms
: Backtransform the set of transformed parameters
Johannes Ranke
SFO_SFO <- mkinmod( parent = list(type = "SFO", to = "m1", sink = TRUE), m1 = list(type = "SFO")) # Fit the model to the FOCUS example dataset D using defaults fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE) fit.s <- summary(fit) # Transformed and backtransformed parameters print(fit.s$par, 3) print(fit.s$bpar, 3) ## Not run: # Compare to the version without transforming rate parameters fit.2 <- mkinfit(SFO_SFO, FOCUS_2006_D, transform_rates = FALSE, quiet = TRUE) fit.2.s <- summary(fit.2) print(fit.2.s$par, 3) print(fit.2.s$bpar, 3) ## End(Not run) initials <- fit$start$value names(initials) <- rownames(fit$start) transformed <- fit$start_transformed$value names(transformed) <- rownames(fit$start_transformed) transform_odeparms(initials, SFO_SFO) backtransform_odeparms(transformed, SFO_SFO) ## Not run: # The case of formation fractions SFO_SFO.ff <- mkinmod( parent = list(type = "SFO", to = "m1", sink = TRUE), m1 = list(type = "SFO"), use_of_ff = "max") fit.ff <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE) fit.ff.s <- summary(fit.ff) print(fit.ff.s$par, 3) print(fit.ff.s$bpar, 3) initials <- c("f_parent_to_m1" = 0.5) transformed <- transform_odeparms(initials, SFO_SFO.ff) backtransform_odeparms(transformed, SFO_SFO.ff) # And without sink SFO_SFO.ff.2 <- mkinmod( parent = list(type = "SFO", to = "m1", sink = FALSE), m1 = list(type = "SFO"), use_of_ff = "max") fit.ff.2 <- mkinfit(SFO_SFO.ff.2, FOCUS_2006_D, quiet = TRUE) fit.ff.2.s <- summary(fit.ff.2) print(fit.ff.2.s$par, 3) print(fit.ff.2.s$bpar, 3) ## End(Not run)