Description Details Objects from the Class Slots Author(s) See Also

Class "opt" stores options for fitting and plotting applicable to all model types

See `kinopt-class`

, `specopt-class`

and
`massopt-class`

for
the specification of fitting/plotting options that are specific to the
class type.

Objects can be created by calls of the form `new("opt", ...)`

or
`opt(...)`

.

- getStartTri
- imagepal
- maxfev

- minFactor
- nnlscrit
- noplotest
- notraces
- optimmethod
- parscale
- residtraces
- selectedtraces
- sumnls
- trilinear
- triStart
- writedata
- writefitivo
- xlim
`algorithm`

:Object of class

`"character"`

that defaults to`algorithm="nls"`

, so that the function`nls`

is used to optimize nonlinear parameters under least squares criteria. Other options are`nls.lm`

:optimize nonlinear parameters under least squares criteria using

`nls.lm`

`optim`

:optimize nonlinear parameters under poisson regression criteria with the Nelder-Mead algorithm in

`optim`

; if this option is used then it MUST be used in conjunction with`nnls=TRUE`

. Currently, it must also be used with`stderrclp=FALSE`

.

`nnls`

:Object of class

`"logical"`

that defaults to`FALSE`

. If`nnls=TRUE`

, constrain the conditionally linear parameters to nonnegativity via a nonnegative least squares algorithm as implemented via the function`nnls`

from the package by the same name.`writecon`

:Object of class

`"logical"`

that defaults to`FALSE`

; if true then concentrations are written to a txt file; row labels are`x`

`writespec`

:Object of class

`"logical"`

that defaults to`FALSE`

; if`TRUE`

then spectra are written to a txt file; row labels are`x2`

`writenormspec`

:Object of class

`"logical"`

that defaults to`FALSE`

; if`TRUE`

then normalized spectra are written to a txt file; row labels are`x2`

`writefit`

:Object of class

`"logical"`

that defaults to`FALSE`

; if`TRUE`

then fit is written to a txt file; row and column labels are`x`

and`x2`

`writeclperr`

:Object of class

`"logical"`

that defaults to FALSE; if true then the error bars for clp are written to a txt file. This option is only sensible with`stderrclp=TRUE`

.`output`

:Object of class

`"character"`

that defaults to`"ps"`

, which means that plots written to file are postscript. Alternatively, specify`output = "pdf"`

, and plots are written as pdf files`addfilename`

:Object of class

`"logical"`

that, for each data file, tries to add the filename to plots associated with output for that data.`residplot`

:Object of class

`"logical"`

defaults to`FALSE`

; if`TRUE`

generate a plot of residuals in a separate window.`adddataimage`

:Object of class

`"logical"`

defaults to`FALSE`

; if`TRUE`

adding imageplot of data in summary plot.`plot`

:Object of class

`"logical"`

that defaults to`TRUE`

; if`FALSE`

then do not write output in the form of plots and other windows to the screen.`divdrel`

:Object of class

`"logical"`

that defaults to`FALSE`

; if`TRUE`

, plot traces and concentration profiles divided by the dataset scaling parameters where they apply; this allows for the fit of datasets having different intensities on the same scale.`plotkinspec`

:Object of class

`"logical"`

that defaults to`FALSE`

; if`TRUE`

, generates a separate plot of the spectra associated with the components that are not a part of a coherent artifact/scatter model.`superimpose`

:Object of class

`"vector"`

containing dataset indices whose results should be superimposed in plots`xlab`

:Object of class

`"character"`

containing label for x-axis, e.g.,`"nanoseconds"`

or`"picoseconds"`

`ylab`

:Object of class

`"character"`

containing label for y-axis, e.g.,`"wavelength"`

`title`

:Object of class

`"character"`

containing title to write at the top of plots.`makeps`

:Object of class

`"character"`

containing prefix to plot files written to postscript; if present postscript will be written. Note that this string is also used as the preffix of txt output files`linrange`

:Object of class

`"numeric"`

giving linear range of time axis for plotting; time will be plotted linearly from -linrange to linrange and plotted on a logarithmic (base 10) axis elsewhere`summaryplotrow`

:Object of class

`"numeric"`

giving number of rows in summary plot; defaults to`4`

`summaryplotcol`

:Object of class

`"numeric"`

giving number of columns in summary plot; defaults to`4`

`iter`

:Object of class

`"numeric"`

giving number of iterations to optimize model parameters; if`nls=FALSE`

so that the Levenberg-Marquardt algorithm is applied, then`iter`

is interpretted as the maximum number of residual function evaluations (see the help page of the function`nls.lm`

for details)`paropt`

:Object of class

`"list"`

of graphical parameters in format`par(...)`

to apply to plots.`stderrclp`

:Object of class

`"logical"`

that defaults to`FALSE`

; if`TRUE`

, estimates of the standard error of conditionally linear parameters are made`addest`

:Object of class

`"vector"`

containing character strings of which parameter estimates should be added to the summary plot, e.g.,`addest = c("kinpar", "irfpar")`

- kinspecerr
Object of class

`"logical"`

that defaults to`FALSE`

; if`TRUE`

, add standard error estimates to the clp a plot generated with`kinspecest=TRUE`

or`plotkinspec=TRUE`

. This option can only be used if the estimates were generated during fitting via the option`stderrclp=TRUE`

- xlimspec
Object of class

`"vector"`

that defaults to`vector()`

; if changed, it should specify the desired x-limits of the plot of clp- ylimspec
Object of class

`"vector"`

that defaults to`vector()`

; if changed, it should specify the desired y-limits of the plot of clp. In the case of plotting the results of FLIM image analysis,`ylimspec`

can be used to determine the range used in the image plot of lifetimes.- ylimspecplus
Object of class

`"vector"`

that defaults to`vector()`

; if changed, the first value should specify a vector to add to the y-limits of the plot of clp- samespecline
Object of class

`"logical"`

that defaults to`FALSE`

; if`TRUE`

, then the line-type for clp is the same for all datasets- specinterpol
Object of class

`"logical"`

that defaults to`FALSE`

; if`TRUE`

, use spline instead of lines between the points representing estimated clp- specinterpolpoints
Object of class

`"logical"`

that defaults to`TRUE`

; if`TRUE`

, add points representing the actual estimates for clp to plots of the curves respresenting smoothed clp- specinterpolseg
Object of class

`"numeric"`

that defaults to`50`

; represents the number of segments used in a spline-based representation of clp- specinterpolbspline
Object of class

`"logical"`

that defaults to`FALSE`

; determines whether a B-spline based representation of clp is used (when`specinterpol=TRUE`

) or a piecewise polynomial representation- normspec
Object of class

`"logical"`

that determines whether clp are normalized in plots- writespecinterpol
Object of class

`"logical"`

that defaults to`FALSE`

; if`TRUE`

, a spline-based representation of clp is written to ASCII files- nlsalgorithm
Object of class

`"character"`

that defaults to`"default"`

and determines the algorithm used by`nls`

, if`nls`

is used in optimization. See`help(nls)`

for other possibilities, such as`"port"`

, which is more stable with respect to starting values but requires more time.- ltyfit
Object of class

`"numeric"`

if given, sets the line type of the fit in plots of the fit/data; see`lty`

in`help(par)`

for options.- ltydata
Object of class

`"numeric"`

if given, sets the line type of the data in plots of the fit/data; see`lty`

in`help(par)`

for options.- colfit
Object of class

`"vector"`

if given, sets the color of the fit corresponding to each dataset in plots of the fit/data; see`col`

in`help(par)`

for options. If given`length(colfit)`

must be equal to the number of datasets in the analysis- coldata
Object of class

`"vector"`

if given, sets the color of the data for each dataset in plots of the fit/data; see`col`

in`help(par)`

for options. If given,`length(coldata)`

must be equal to the number of datasets in the analysis

Katharine M. Mullen, Ivo H. M. van Stokkum

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