diff options
Diffstat (limited to 'man')
| -rw-r--r-- | man/mkinfit.Rd | 64 |
1 files changed, 56 insertions, 8 deletions
diff --git a/man/mkinfit.Rd b/man/mkinfit.Rd index 445bce2e..a080f8ae 100644 --- a/man/mkinfit.Rd +++ b/man/mkinfit.Rd @@ -20,7 +20,9 @@ mkinfit(mkinmod, observed, plot = FALSE, quiet = FALSE, err = NULL, weight = "none", scaleVar = FALSE, atol = 1e-8, rtol = 1e-10, n.outtimes = 100, - trace_parms, ...) + reweight.method = NULL, + reweight.tol = 1e-8, reweight.max.iter = 10, + trace_parms = FALSE, ...) } \arguments{ \item{mkinmod}{ @@ -94,7 +96,7 @@ mkinfit(mkinmod, observed, \emph{error} estimates, used to weigh the residuals (see details of \code{\link{modCost}}); if \code{NULL}, then the residuals are not weighed. } - \item{weight}{only if \code{err}=\code{NULL}: how to weigh the + \item{weight}{only if \code{err}=\code{NULL}: how to weight the residuals, one of "none", "std", "mean", see details of \code{\link{modCost}}. } \item{scaleVar}{ @@ -115,6 +117,23 @@ mkinfit(mkinmod, observed, the numerical solver if that is used (see \code{solution} argument. The default value is 100. } + \item{reweight.method}{ + The method used for iteratively reweighting residuals, also known + as iteratively reweighted least squares (IRLS). Default is NULL, + the other method implemented is called "obs", meaning that each + observed variable is assumed to have its own variance, this is + estimated from the fit and used for weighting the residuals + in each iteration until convergence of this estimate up to + \code{reweight.tol} or up to the maximum number of iterations + specified by \code{reweight.maxiter}. + } + \item{reweight.tol}{ + Tolerance for convergence criterion for the variance components + in IRLS fits. + } + \item{reweight.max.iter}{ + Maximum iterations in IRLS fits. + } \item{trace_parms}{ Should a trace of the parameter values be listed? } @@ -123,8 +142,14 @@ mkinfit(mkinmod, observed, } } \value{ - A list with "mkinfit" and "modFit" in the class attribute. - A summary can be obtained by \code{\link{summary.mkinfit}}. + A list with "mkinfit" and "modFit" in the class attribute. + A summary can be obtained by \code{\link{summary.mkinfit}}. +} +\note{ + The implementation of iteratively reweighted least squares is inspired by the + work of the KinGUII team at Bayer Crop Science (Walter Schmitt and Zhenglei + Gao). A similar implemention can also be found in CAKE 2.0, which is the + other GUI derivative of mkin, sponsored by Syngenta. } \author{ Johannes Ranke <jranke@uni-bremen.de> @@ -136,7 +161,6 @@ SFO_SFO <- mkinmod( m1 = list(type = "SFO")) # Fit the model to the FOCUS example dataset D using defaults fit <- mkinfit(SFO_SFO, FOCUS_2006_D) -str(fit) summary(fit) # Use stepwise fitting, using optimised parameters from parent only fit, FOMC @@ -147,9 +171,10 @@ FOMC_SFO <- mkinmod( m1 = list(type = "SFO")) # Fit the model to the FOCUS example dataset D using defaults fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_2006_D) -# Use starting parameters from parent only FOMC fit (not really needed in this case) -fit.FOMC = mkinfit(FOMC, FOCUS_2006_D) -fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_2006_D, parms.ini = fit.FOMC$bparms.ode, plot=TRUE) +# Use starting parameters from parent only FOMC fit +fit.FOMC = mkinfit(FOMC, FOCUS_2006_D, plot=TRUE) +fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_2006_D, + parms.ini = fit.FOMC$bparms.ode, plot=TRUE) } # Use stepwise fitting, using optimised parameters from parent only fit, SFORB @@ -162,6 +187,29 @@ fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D) # Use starting parameters from parent only SFORB fit (not really needed in this case) fit.SFORB = mkinfit(SFORB, FOCUS_2006_D) fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D, parms.ini = fit.SFORB$bparms.ode, plot=TRUE) + +# Weighted fits, including IRLS +SFO_SFO.ff <- mkinmod(parent = list(type = "SFO", to = "m1"), + m1 = list(type = "SFO"), use_of_ff = "max") +f.noweight <- mkinfit(SFO_SFO.ff, FOCUS_2006_D) +summary(f.noweight) +f.irls <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, reweight.method = "obs") +summary(f.irls) +f.w.mean <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, weight = "mean") +summary(f.w.mean) +f.w.mean.irls <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, weight = "mean", + reweight.method = "obs") +summary(f.w.mean.irls) + +# Manual weighting +dw <- FOCUS_2006_D +errors <- c(parent = 2, m1 = 1) +dw$err.man <- errors[FOCUS_2006_D$name] +f.w.man <- mkinfit(SFO_SFO.ff, dw, err = "err.man") +summary(f.w.man) +f.w.man.irls <- mkinfit(SFO_SFO.ff, dw, err = "err.man", + reweight.method = "obs") +summary(f.w.man.irls) } \keyword{ models } \keyword{ optimize } |