summary.mpl: Summary Method for 'mpl' Objects
In hoa: Higher Order Likelihood Inference

Description Usage Arguments Details Value See Also Examples

Returns a summary list for objects of class mpl.

1 2	## S3 method for class 'mpl' summary(object, correlation = FALSE, digits = NULL, ...)

`object`	a fitted `mpl` object, that is, the result of a call to `mpl.nlreg`.
`correlation`	logical argument. If `TRUE`, the (asymptotic) correlation matrix for the parameter estimates is computed; default is `FALSE`.
`digits`	the number of significant digits to be printed. Defaults to `NULL`.
`...`	absorbs any additional argument.

This function is a method for the generic function summary for class mpl. It can be invoked by calling summary for an object of the appropriate class, or directly by calling summary.mpl regardless of the class of the object.

A list is returned with the following components:

`varPar`	the maximum adjusted profile likelihood estimates of the variance parameters.
`coefficients`	the constrained MLEs of the regression coefficients given the maximum adjusted profile likelihood estimates of the variance parameters.
`offset`	the values passed through the `offset` argument in the call to `mpl.nlreg` that generated the `mpl` object and to which the variance parameters were fixed.
`varParMLE`	the MLEs of the variance parameters.
`coefMLE`	the MLEs of the regression coefficients.
`varParCov`	the (asymptotic) covariance matrix of the variance parameters, that is, the corresponding block in the inverse of the observed information matrix.
`coefCov`	the (asymptotic) covariance matrix of the regression coefficients, that is, the corresponding block in the inverse of the observed information matrix.
`lmp`	the adjusted profile log likelihood from the fit.
`lp`	the profile log likelihood from the fit.
`stats`	the indicator of which higher order solution was used.
`formula`	the model formula.
`meanFun`	the formula expression of the mean function.
`varFun`	the formula expression of the variance function.
`data`	a list representing a summary of the original data with the following components. `'offset name'` the predictor variable with no duplicated value. `repl` the number of replicates available for each value of the predictor. `dupl` a vector of the same length than the predictor variable indicating the position of each data point in the offset name component. `t1` the sum of the reponses for each design point in the offset name component. `t2` the sum of the squared responses for each design point in the offset name component.
`nobs`	the number of observations.
`iter`	the number of interations needed for convergence; only if `offset` was not `NULL` in the call to `mpl.nlreg` which generated `object`.
`call`	an image of the call to `mpl.nlreg`, but with all the arguments explicitly named.
`ws`	the workspace component of the original `nlreg object` plus the following components: `corr` a logical value indicating whether the correlation matrix should be printed. `digits` the number of significant digits to be printed.

mpl.object, nlreg.object, summary

data(metsulfuron)
metsulfuron.nl <- 
    nlreg( formula = log(area) ~ log( b1+(b2-b1) / (1+(dose/b4)^b3) ), 
           weights = ~ ( 1+dose^exp(g) )^2, data = metsulfuron, hoa = TRUE, 
           start = c(b1 = 138, b2 = 2470, b3 = 2, b4 = 0.07, g = log(0.3)) )
##
metsulfuron.mpl <- mpl( metsulfuron.nl, trace = TRUE )
summary( metsulfuron.mpl, corr = FALSE )