profile.nls {stats} | R Documentation |
Investigates the profile log-likelihood function for a fitted model of
class "nls"
.
## S3 method for class 'nls' profile(fitted, which = 1:npar, maxpts = 100, alphamax = 0.01, delta.t = cutoff/5, ...)
fitted |
the original fitted model object. |
which |
the original model parameters which should be profiled. This can be a numeric or character vector. By default, all non-linear parameters are profiled. |
maxpts |
maximum number of points to be used for profiling each parameter. |
alphamax |
highest significance level allowed for the profile t-statistics. |
delta.t |
suggested change on the scale of the profile t-statistics. Default value chosen to allow profiling at about 10 parameter values. |
... |
further arguments passed to or from other methods. |
The profile t-statistics is defined as the square root of change in sum-of-squares divided by residual standard error with an appropriate sign.
A list with an element for each parameter being profiled. The elements are data-frames with two variables
par.vals |
a matrix of parameter values for each fitted model. |
tau |
the profile t-statistics. |
Of the original version, Douglas M. Bates and Saikat DebRoy
Bates, D. M. and Watts, D. G. (1988), Nonlinear Regression Analysis and Its Applications, Wiley (chapter 6).
nls
, profile
, plot.profile.nls
# obtain the fitted object fm1 <- nls(demand ~ SSasympOrig(Time, A, lrc), data = BOD) # get the profile for the fitted model: default level is too extreme pr1 <- profile(fm1, alpha = 0.05) # profiled values for the two parameters ## IGNORE_RDIFF_BEGIN pr1$A pr1$lrc ## IGNORE_RDIFF_END # see also example(plot.profile.nls)