summary.nlreg.profile {nlreg} | R Documentation |
Summary Method for Objects of Class ‘nlreg.profile’
Description
Returns a summary list for objects of class nlreg.profile
.
Usage
## S3 method for class 'nlreg.profile'
summary(object, alpha = 0.05, twoside = TRUE, digits = NULL, ...)
Arguments
object |
a |
alpha |
a vector of levels for confidence intervals; the default is
|
twoside |
a logical value. If |
digits |
the number of significant digits to be printed. |
... |
absorbs any additional argument. |
Details
This function is a method for the generic function
summary
for objects of class
nlreg.profile
. It can be invoked by calling summary
or directly summary.nlreg.profile
for an object of the
appropriate class.
Value
A list is returned with the following components:
CI |
a matrix with |
inf.sk , np.sk , inf.fr , np.fr |
the information and nuisance parameters aspects, that is, the two
terms into which the higher order adjustment leading to the
|
mle |
a numerical vector giving the MLE of the parameter of interest and its standard error. |
offset |
character string giving the name of the interest parameter. |
twoside |
a logical value indicating whether two-sided or one-sided confidence intervals were calculated. |
points |
the number of output points at which the considered statistics were calculated exactly. |
n |
the approximate number of points used in the spline interpolation of the considered statistics. |
hoa |
a logical value indicating whether higher order solutions were calculated. |
digits |
the number of significant digits to be printed. |
call |
an image of the call that produced the object, but with all arguments named. |
... |
absorbs additional arguments. |
References
Fraser, D.A.S., Reid, N. and Wu, J. (1999). A simple general formula for tail probabilities for frequentist and Bayesian inference. Biometrika, 86, 249–264.
Skovgaard, I. (1996) An explicit large-deviation approximation to one-parameter tests. Bernoulli, 2, 145–165.
See Also
nlreg.profile.object
,
profile.nlreg
,
summary
Examples
data(metsulfuron)
metsulfuron.nl <-
nlreg( formula = log(area) ~ log( b1+(b2-b1) / (1+(dose/b4)^b3) ),
weights = ~ ( 1+dose^exp(g) )^2, data = metsulfuron,
start = c(b1 = 138, b2 = 2470, b3 = 2, b4 = 0.07, g = log(0.3)),
hoa = TRUE )
##
metsulfuron.prof <- profile( metsulfuron.nl, offset = g, trace = TRUE )
summary( metsulfuron.prof, alpha = c(0.9, 0.95) )