nlr (version 0.1-3)

jaclev: Jacobian Leverage for nonlinear regression.

Description

Compute the Jacobian Leverage, generalized for nonlinear case.

Usage

jaclev(gradient, hessian, rsd)

Arguments

gradient

\(n \times p\) gradient of nonlinear function.

hessian

three simentional \(n \times p \times p\) of hessian of nonlinear regression function.

rsd

\(n \times 1\) residual vector.

Value

\(n \times n\) matrix of jacobian leverages.

Details

Jacobian leverage, generalized form of hat matrix for nonlinear regression.

References

Laurent. R. T. ST., and Cook. R. D. (1992). Leverage and Superleverage in Nonlinear Regression, Journal of the American Statistical Association 87(420): 985-990.

See Also

nl.fitt, nl.fitt.gn

Examples

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