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| author | Johannes Ranke <jranke@uni-bremen.de> | 2020-05-12 19:10:32 +0200 |
|---|---|---|
| committer | Johannes Ranke <jranke@uni-bremen.de> | 2020-05-12 19:10:32 +0200 |
| commit | 36bc31c52cbe4b686f5562e21ee110380481dff8 (patch) | |
| tree | f872beb978159d6f69b60505030fc1beedc1b747 /man | |
| parent | 20f235860c3d5a9c6319c516637021e02ecb6cae (diff) | |
Another documentation update
Diffstat (limited to 'man')
| -rw-r--r-- | man/mkinfit.Rd | 19 |
1 files changed, 8 insertions, 11 deletions
diff --git a/man/mkinfit.Rd b/man/mkinfit.Rd index 5a2b3e53..b8d44fba 100644 --- a/man/mkinfit.Rd +++ b/man/mkinfit.Rd @@ -94,12 +94,11 @@ differential equations is based on the spectral decomposition of the coefficient matrix in cases that this is possible. If set to "deSolve", a numerical ode solver from package \code{\link{deSolve}} is used. If set to "analytical", an analytical solution of the model is used. This is only -implemented for simple degradation experiments with only one state -variable, i.e. with no metabolites. The default is "auto", which uses -"analytical" if possible, otherwise "deSolve" if a compiler is present, -and "eigen" if no compiler is present and the model can be expressed using -eigenvalues and eigenvectors. This argument is passed on to the helper -function \code{\link{mkinpredict}}.} +implemented for relatively simple degradation models. The default is +"auto", which uses "analytical" if possible, otherwise "deSolve" if a +compiler is present, and "eigen" if no compiler is present and the model +can be expressed using eigenvalues and eigenvectors. This argument is +passed on to the helper function \code{\link{mkinpredict}}.} \item{method.ode}{The solution method passed via \code{\link{mkinpredict}} to \code{\link{ode}} in case the solution type is "deSolve". The default @@ -154,11 +153,9 @@ the error model. If the error model is "const", unweighted nonlinear least squares fitting ("OLS") is selected. If the error model is "obs", or "tc", the "d_3" algorithm is selected. -The algorithm "d_3" will directly minimize the negative log-likelihood and -\itemize{ -\item independently - also use the three step algorithm described below. The -fit with the higher likelihood is returned. -} +The algorithm "d_3" will directly minimize the negative log-likelihood +and independently also use the three step algorithm described below. +The fit with the higher likelihood is returned. The algorithm "direct" will directly minimize the negative log-likelihood. |