modpar: Estimate Values to be Used for Fixed FlexParamCurve...
In FlexParamCurve: Tools to Fit Flexible Parametric Curves
Description
Usage
Arguments
Details
Value
Note
Author(s)
Examples
Description
This function creates the object pnmodelparams
which holds estimates of values for all 8 FlexParamCurve
parameters used for fitting and solving positive-negative Richards curves with
SSposnegRichards and posnegRichards.eqn,
respectively.
Usage
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modpar(x,
y,
pn.options = NA,
first.y = NA,
x.at.first.y = NA,
last.y = NA,
x.at.last.y = NA,
twocomponent.x = NA,
verbose = FALSE,
force8par = FALSE,
force4par = FALSE,
suppress.text = FALSE,
taper.ends = 0.45,
width.bounds = 1,
bounds.error = FALSE,
Envir = .GlobalEnv,
force.nonmonotonic = FALSE,
...)
Arguments
x
a numeric vector of primary predictor variable
y
a numeric vector of response variable
first.y
the value of y at minimum x when it is required to be constrained
x.at.first.y
the final value of x - 0 value is used if not specified when last.y is not NA
last.y
the value of y at maximum x when it is required to be constrained
x.at.last.y
the final value of x - must be specified if last.y is not NA
twocomponent.x
a numerical specifying the x-value (e.g. age) of intersection if a double model of
two separate components is to be fitted. Alternatively a logical of value
= TRUE if the same type of model is to be fitted but the x of
intersection is unknown
verbose
logical indicating whether information on successful optimization and
parameters should be returned during when using SSposnegRichards
force8par
logical specifying whether parameters of the negative Richards
curve should be set to defaults if they cannot be estimated
force4par
logical specifying whether parameters of the negative Richards
should be ignored - effectively using simple Richards curve
pn.options
character string specifying name of list object populated with starting
parameter estimates, fitting options and bounds or the destination for modpar to write a new list
suppress.text
logical specifying whether modpar should return descriptive text to the screen during execution
taper.ends
numeric representing the proportion of the range of the x variable for which data are extended at
the two ends of the data set. This is used in initial estimation (prior to optim and nls optimizations) and can
speed up subsequent optimizations by imposing a more pronounced S-shape to both first and second curves. Defaults to 0.45.
width.bounds
a numeric indicating the proportion of the usual width of parameter bounds to be imposed during optimizations.
Large values may slow or terminate computations, however they could better accomodate data in which different levels exhibit very different
parameter values.
bounds.error
a logical. If true parameter estimation will terminate if initial estimation of parameters leads to
values outside specified bounds in pn.options. If false, more appropriate bounds will be determined automatically.
Envir
a valid R environment to find pn.options in and export any output to, by default this is the global environment
force.nonmonotonic
if set to TRUE fixed recessional parameter estimates will be used for the two monotonic equations
(modno #12 or #32), otherwise these two models will use RAsym = 0, Ri = 0, Rk = 1, RM = 1 to prevent non-monotonic relationships
in these cases.
...
additional optional arguments to be passed to nlsList
Details
This function creates a formatted list object as named by the argument pn.options. This list
holds estimates of values for all 8 FlexParamCurve parameters, fitting options and parameter bounds used for
fitting and solving double-Richards curves with SSposnegRichards and posnegRichards.eqn,
respectively. Parameter bounds are the maximum and minimum parameters values that can be used by optim
and nls during parameter estimation. For definitions of parameters see either SSposnegRichards
or posnegRichards.eqn. The list is written automatically by the function (to ".pntemplist") but it is
also output as a return value for assignation and subsequent use in the usual way [myoptions<- change.pnparameters(...)].
Estimates are produced by fitting positive-negative or double Richards curves in
nls using
SSposnegRichards for the full 8 parameter model (R1).
If this fails, the function getInitial is called to
attempt to produce initial estimates using the same 8 parameter model.
If this also fails, estimates are attempted in the same way using the
4 parameter (positive only) model (R12). In this case, only the positive
parameters are returned (NAs are substituted for negative parameters)
unless argument force8par=TRUE, in which case negative parameters are
defaulted to: RAsym = 0.05*Asym, Rk = K, Ri = Infl, RM = M.
This function can now fit biphasic (and more generally
double-Richards) curves, where the final curve is effectively either two positive curves
or two negative curves, as well as negative-positive curves. This functionality is default
and does not need to be specified.
Parameter bounds estimated here for use in optim and nls
fits within SSposnegRichards are
applicable to a wide range of curves, although user may
change these manually in list object specified by pn.options.
Bounds are estimated by modpar by adding or subtracting multiples
of fixed parameter values to estimated mean parameter values:
-Asym*0.5 and +Asym*2.5,
-K*0.5 and +K*0.5,
-Infl*2.5 and +Infl*10
-M*2 and +M*2
-RAsym*0.5 and +RAsym*2.5,
-Rk*0.5 and +Rk*0.5,
-Ri*2.5 and +Ri*5
-RM*2 and +RM*2.
Use force8par = TRUE if initial call to modpar produces estimates for
only 4 parameters and yet an 8 parameter model is desired for SSposnegRichards
or posnegRichards.eqn.
Use force4par = TRUE if you desire to produces estimates only for the four parameters of
a single Richards curves. This should also be used if you wish to fit simple logistic
Gompertz or von Bertalanffy curves: see SSposnegRichards for more details. If
the specified model in subsequent eqnSSposnegRichards, model selection or ploting calls
is monotonic (i.e. contains no recession parameters: modno= 12 or 32) recessional parameters
will not be included for these two models unless "force.nonmonotonic" option is TRUE,
in the specified pn.options list object, in which case parameters will be drawn from the specified
pn.options list object.
When specified, first.y and last.y are saved in list object specified by pn.options to instruct
SSposnegRichards to add this as the first or last value of the response, respectively,
during estimation.
To fit two-component double-curves, in which one curve equation is used up to (and including)
the x of intersection and a separate equation is used for x-values greater than the x of intersection
the argument twocomponent.x should be set to the value for the x of intersection. If this argument
is anything other than NA then a two-component model will be fitted when SSposnegRichards
is called. This option will be saved in list object specified by pn.options and can be changed at will.
taper.ends can be used to speed up optimization as it extends the dataset at maximum and minimum extremes
of x by repeatedly pasting the y values at these extremes for a specified proportion of the range of x.
taper.ends is a numeric value representing the proportion of the range of x values are extended for and
defaults to 0.45 (45
tend towards a zero slope this is a suitable values. If tapered ends are not desirable then choose taper.ends = 0.
If the argument verbose = TRUE then details concerning the optimization processes within
SSposnegRichards are printed on screen whenever SSposnegRichards is called.
These include whether optimization of the first or second parts of the curve or simultaneous optimizations
are successful, if these have been further refined by nls, whether default parameters were used or the
parameterization was aborted and what parameter values were finally exported by SSposnegRichards.
This option will be saved in the list object specified by pn.options and can be changed at will.
Value
a list of estimated fixed values for all
above arguments
Note
Version 1.5 saves many variables, and internal variables in the package environment:
FlexParamCurve:::FPCEnv. By default, the pn.options file is copied to the environment
specified by the functions (global environment by default). Model selection routines
also copy from FPCenv to the global environment all nlsList models fitted during
model selection to provide backcompatibility with code for earlier versions. The user
can redirect the directory to copy to by altering the Envir argument when calling the
function.
Author(s)
Stephen Oswald <steve.oswald@psu.edu>
Examples
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# estimate fixed parameters use data object posneg.data
modpar(posneg.data$age, posneg.data$mass, pn.options = "myoptions")
# estimate fixed parameters use data object posneg.data (only first
# 4 group levels for example's sake) and specify a fixed hatching
# mass for curve optimization using \code{\link{SSposnegRichards}}
modpar(posneg.data$age, posneg.data$mass, pn.options = "myoptions")
subdata <- subset(posneg.data,posneg.data$id == as.character(36)
| posneg.data$id == as.character(9)
| posneg.data$id == as.character(32)
| posneg.data$id == as.character(43))
richardsR22.lis <- nlsList(mass ~ SSposnegRichards(age, Asym = Asym,
K = K, Infl = Infl, RAsym = RAsym, Rk = Rk, Ri = Ri,
modno = 22, pn.options = "myoptions"), data = subdata)
# force an 8 parameter estimate on logistic data
modpar(logist.data$age,logist.data$mass,force8par=TRUE, pn.options = "myoptions")
# force an 4 parameter model on logistic data
modpar(logist.data$age,logist.data$mass,force4par=TRUE, pn.options = "myoptions")
# troubleshoot the fit of a model
modpar(posneg.data$age,posneg.data$mass,verbose=TRUE, pn.options = "myoptions")
# fit a two component model - enter your own data in place of "mydata"
# this details an approach but is not run for want of appropriate data
# if x of intersection unknown
## Not run:
modpar(mydata$x,mydata$y,twocomponent.x=TRUE, pn.options = "myoptions")
# if x of intersection = 75
modpar(mydata$x,mydata$y,twocomponent.x=75, pn.options = "myoptions")
richardsR1.nls <- nls(y~ SSposnegRichards(x, Asym = Asym, K = K,
Infl = Infl, M = M, RAsym = RAsym, Rk = Rk, Ri = Ri, RM = RM,
modno = 1, pn.options = "myoptions")
, data = mydata)
## End(Not run)
FlexParamCurve documentation built on May 1, 2019, 11:36 p.m.
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Description Usage Arguments Details Value Note Author(s) Examples
Description
This function creates the object pnmodelparams
which holds estimates of values for all 8 FlexParamCurve
parameters used for fitting and solving positive-negative Richards curves with
SSposnegRichards and posnegRichards.eqn,
respectively.
Usage
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | modpar(x,
y,
pn.options = NA,
first.y = NA,
x.at.first.y = NA,
last.y = NA,
x.at.last.y = NA,
twocomponent.x = NA,
verbose = FALSE,
force8par = FALSE,
force4par = FALSE,
suppress.text = FALSE,
taper.ends = 0.45,
width.bounds = 1,
bounds.error = FALSE,
Envir = .GlobalEnv,
force.nonmonotonic = FALSE,
...)
|
Arguments
x |
a numeric vector of primary predictor variable |
y |
a numeric vector of response variable |
first.y |
the value of y at minimum x when it is required to be constrained |
x.at.first.y |
the final value of x - 0 value is used if not specified when last.y is not NA |
last.y |
the value of y at maximum x when it is required to be constrained |
x.at.last.y |
the final value of x - must be specified if last.y is not NA |
twocomponent.x |
a numerical specifying the x-value (e.g. age) of intersection if a double model of two separate components is to be fitted. Alternatively a logical of value = TRUE if the same type of model is to be fitted but the x of intersection is unknown |
verbose |
logical indicating whether information on successful optimization and parameters should be returned during when using SSposnegRichards |
force8par |
logical specifying whether parameters of the negative Richards curve should be set to defaults if they cannot be estimated |
force4par |
logical specifying whether parameters of the negative Richards should be ignored - effectively using simple Richards curve |
pn.options |
character string specifying name of parameter estimates, fitting options and bounds or the destination for |
suppress.text |
logical specifying whether modpar should return descriptive text to the screen during execution |
taper.ends |
numeric representing the proportion of the range of the x variable for which data are extended at the two ends of the data set. This is used in initial estimation (prior to optim and nls optimizations) and can speed up subsequent optimizations by imposing a more pronounced S-shape to both first and second curves. Defaults to 0.45. |
width.bounds |
a numeric indicating the proportion of the usual width of parameter bounds to be imposed during optimizations. Large values may slow or terminate computations, however they could better accomodate data in which different levels exhibit very different parameter values. |
bounds.error |
a logical. If true parameter estimation will terminate if initial estimation of parameters leads to values outside specified bounds in pn.options. If false, more appropriate bounds will be determined automatically. |
Envir |
a valid R environment to find pn.options in and export any output to, by default this is the global environment |
force.nonmonotonic |
if set to TRUE fixed recessional parameter estimates will be used for the two monotonic equations (modno #12 or #32), otherwise these two models will use RAsym = 0, Ri = 0, Rk = 1, RM = 1 to prevent non-monotonic relationships in these cases. |
... |
additional optional arguments to be passed to nlsList |
Details
This function creates a formatted list object as named by the argument pn.options. This list
holds estimates of values for all 8 FlexParamCurve parameters, fitting options and parameter bounds used for
fitting and solving double-Richards curves with SSposnegRichards and posnegRichards.eqn,
respectively. Parameter bounds are the maximum and minimum parameters values that can be used by optim
and nls during parameter estimation. For definitions of parameters see either SSposnegRichards
or posnegRichards.eqn. The list is written automatically by the function (to ".pntemplist") but it is
also output as a return value for assignation and subsequent use in the usual way [myoptions<- change.pnparameters(...)].
Estimates are produced by fitting positive-negative or double Richards curves in
nls using
SSposnegRichards for the full 8 parameter model (R1).
If this fails, the function getInitial is called to
attempt to produce initial estimates using the same 8 parameter model.
If this also fails, estimates are attempted in the same way using the
4 parameter (positive only) model (R12). In this case, only the positive
parameters are returned (NAs are substituted for negative parameters)
unless argument force8par=TRUE, in which case negative parameters are
defaulted to: RAsym = 0.05*Asym, Rk = K, Ri = Infl, RM = M.
This function can now fit biphasic (and more generally
double-Richards) curves, where the final curve is effectively either two positive curves
or two negative curves, as well as negative-positive curves. This functionality is default
and does not need to be specified.
Parameter bounds estimated here for use in optim and nls
fits within SSposnegRichards are
applicable to a wide range of curves, although user may
change these manually in list object specified by pn.options.
Bounds are estimated by modpar by adding or subtracting multiples
of fixed parameter values to estimated mean parameter values:
-Asym*0.5 and +Asym*2.5,
-K*0.5 and +K*0.5,
-Infl*2.5 and +Infl*10
-M*2 and +M*2
-RAsym*0.5 and +RAsym*2.5,
-Rk*0.5 and +Rk*0.5,
-Ri*2.5 and +Ri*5
-RM*2 and +RM*2.
Use force8par = TRUE if initial call to modpar produces estimates for
only 4 parameters and yet an 8 parameter model is desired for SSposnegRichards
or posnegRichards.eqn.
Use force4par = TRUE if you desire to produces estimates only for the four parameters of
a single Richards curves. This should also be used if you wish to fit simple logistic
Gompertz or von Bertalanffy curves: see SSposnegRichards for more details. If
the specified model in subsequent eqnSSposnegRichards, model selection or ploting calls
is monotonic (i.e. contains no recession parameters: modno= 12 or 32) recessional parameters
will not be included for these two models unless "force.nonmonotonic" option is TRUE,
in the specified pn.options list object, in which case parameters will be drawn from the specified
pn.options list object.
When specified, first.y and last.y are saved in list object specified by pn.options to instruct
SSposnegRichards to add this as the first or last value of the response, respectively,
during estimation.
To fit two-component double-curves, in which one curve equation is used up to (and including)
the x of intersection and a separate equation is used for x-values greater than the x of intersection
the argument twocomponent.x should be set to the value for the x of intersection. If this argument
is anything other than NA then a two-component model will be fitted when SSposnegRichards
is called. This option will be saved in list object specified by pn.options and can be changed at will.
taper.ends can be used to speed up optimization as it extends the dataset at maximum and minimum extremes
of x by repeatedly pasting the y values at these extremes for a specified proportion of the range of x.
taper.ends is a numeric value representing the proportion of the range of x values are extended for and
defaults to 0.45 (45
tend towards a zero slope this is a suitable values. If tapered ends are not desirable then choose taper.ends = 0.
If the argument verbose = TRUE then details concerning the optimization processes within
SSposnegRichards are printed on screen whenever SSposnegRichards is called.
These include whether optimization of the first or second parts of the curve or simultaneous optimizations
are successful, if these have been further refined by nls, whether default parameters were used or the
parameterization was aborted and what parameter values were finally exported by SSposnegRichards.
This option will be saved in the list object specified by pn.options and can be changed at will.
Value
a list of estimated fixed values for all
above arguments
Note
Version 1.5 saves many variables, and internal variables in the package environment:
FlexParamCurve:::FPCEnv. By default, the pn.options file is copied to the environment
specified by the functions (global environment by default). Model selection routines
also copy from FPCenv to the global environment all nlsList models fitted during
model selection to provide backcompatibility with code for earlier versions. The user
can redirect the directory to copy to by altering the Envir argument when calling the
function.
Author(s)
Stephen Oswald <steve.oswald@psu.edu>
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 | # estimate fixed parameters use data object posneg.data
modpar(posneg.data$age, posneg.data$mass, pn.options = "myoptions")
# estimate fixed parameters use data object posneg.data (only first
# 4 group levels for example's sake) and specify a fixed hatching
# mass for curve optimization using \code{\link{SSposnegRichards}}
modpar(posneg.data$age, posneg.data$mass, pn.options = "myoptions")
subdata <- subset(posneg.data,posneg.data$id == as.character(36)
| posneg.data$id == as.character(9)
| posneg.data$id == as.character(32)
| posneg.data$id == as.character(43))
richardsR22.lis <- nlsList(mass ~ SSposnegRichards(age, Asym = Asym,
K = K, Infl = Infl, RAsym = RAsym, Rk = Rk, Ri = Ri,
modno = 22, pn.options = "myoptions"), data = subdata)
# force an 8 parameter estimate on logistic data
modpar(logist.data$age,logist.data$mass,force8par=TRUE, pn.options = "myoptions")
# force an 4 parameter model on logistic data
modpar(logist.data$age,logist.data$mass,force4par=TRUE, pn.options = "myoptions")
# troubleshoot the fit of a model
modpar(posneg.data$age,posneg.data$mass,verbose=TRUE, pn.options = "myoptions")
# fit a two component model - enter your own data in place of "mydata"
# this details an approach but is not run for want of appropriate data
# if x of intersection unknown
## Not run:
modpar(mydata$x,mydata$y,twocomponent.x=TRUE, pn.options = "myoptions")
# if x of intersection = 75
modpar(mydata$x,mydata$y,twocomponent.x=75, pn.options = "myoptions")
richardsR1.nls <- nls(y~ SSposnegRichards(x, Asym = Asym, K = K,
Infl = Infl, M = M, RAsym = RAsym, Rk = Rk, Ri = Ri, RM = RM,
modno = 1, pn.options = "myoptions")
, data = mydata)
## End(Not run)
|
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