nlr (version 0.1-3)

pInf: Parameter Inference for classic nonlinear regression.

Description

Parameter inference for classic nonliner regression. It work same as parInfer method of nl.fitt, calculate covariance matrix of parameters and their confidence interval using gradient as design matrix.

Usage

pInf(object, confidence = 0.95)

Arguments

object

Object type nl.fitt or any other of its child objects such as nl.fitt.gn, nl.fitt.rob, nl.fitt.rgn.

confidence

Confidence probability.

Value

covmat:

Covariance matrix of nonlinear model function parameters.

corrmat

Correlation matrix of nonlinear model function parameters.

parstdev:

Standard deviation of nonlinear model function parameter. It is square root of diagonal of covmat.

CI:

Confidence interval for nonlinear model function parameter.

Details

For computing the covariance matrix of a nonlinear regression parameter, the gradient of function with respect to parameters is consider as design matrix and linear regression formulas apply for computing covariances and confidence intervals.

References

Seber, G., A. F. and Wild, C. J. (2003). Nonlinear Regression. New York: John Wiley & Sons, Inc.

Lim, C., Sen, P. K., Peddada, S. D. (2010). Statistical inference in nonlinear regression under heteroscedasticity. Sankhya B 72:202-218.

See Also

nl.fitt, nl.fitt.gn, nl.fitt.rob, nl.fitt.rgn

Examples

# NOT RUN {
## The function is currently defined as
"pInf"
# }