nlreg.object: Nonlinear Heteroscedastic Model Object

Description Arguments Generation Methods Note See Also

Description

Class of objects returned when fitting a nonlinear heteroscedastic model.

Arguments

The following components must be included in a nlreg object:

coef

the MLEs of the regression coefficients, that is, of the parameters appearing in the right-hand side of the formula argument in the call that generated the nlreg object.

varPar

the MLEs of the variance parameters appearing in the weights argument of the call that generated the nlreg object. If this argument was missing, the MLE of \code{log(s^2)}, the logarithm of the constant variance, is returned.

offset

a numerical vector with a single named element indicating the parameter of interest and the value to which it was fixed while fitting the nonlinear model.

logLik

the log likelihood from the fit.

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.

fitted

the fitted values, that is, the mean function evaluated at each data point.

weights

the variance function evaluated at each data point.

residuals

the response/standardized residuals from the fit.

start

the starting values used to initialize the fitting routine.

call

an image of the call to nlreg, but with all the arguments explicitly named.

ws

a list containing information that is used in subsequent calculations with the following components:

allPar

the MLEs of all parameters.

homVar

a logical value indicating whether the variance function is constant.

xVar

a logical value indicating whether the variance function depends on the predictor variable.

hoa

the value of the hoa argument in the call that generated the nlreg object.

missingData

a logical value indicating whether the data argument was missing in the call that generated the nlreg object.

frame

the name of the data frame if specified in the call to nlreg.

iter

the number of iteration required until convergence (only for non constant variance function).

md

a function definition that returns the first two derivatives of the mean function if hoa = TRUE in the function call that generated the nlreg object.

vd

a function definition that returns the first two derivatives of the variance function if hoa = TRUE in the function call that generated the nlreg object.

Generation

This class of objects is returned by the nlreg function to represent a fitted nonlinear heteroscedastic model. Class nlreg inherits from class nls, which represents a homoscedastic nonlinear model fit.

Methods

Objects of this class have methods for the functions print, summary, fitted among others.

Note

The residuals, fitted values and coefficients should be extracted by the generic functions of the same name, rather than by the $ operator.

The data and ws components are not intended to be directly accessed by users, but rather contain information invoked by functions such as profile and nlreg.diag.

See Also

nlreg, nls


nlreg documentation built on Jan. 30, 2019, 5:04 p.m.