Learn R Programming

hisemi (version 1.1-0)

NRupdate: Utility function performing Newton-Raphson algorithm updates

Description

Utility function performing Newton-Raphson algorithm updates for penLik.EMNewton

Usage

NRupdate(f, starts, gradient, hessian, ..., ridge0 = 1e-06, 
        tolerance = sqrt(.Machine$double.eps), 
        iter.max = 1500, halving.max = Inf, relative = FALSE, 
        return.hessian = FALSE, debugging = FALSE)

Arguments

f

Objective function to be minimized

starts

A numeric vector of starting values

gradient

The gradient function of f

hessian

The Hessian function of f

Additional arguments to be passed to f

ridge0

A small ridge factor; obsolete. Current version uses nearPD to stabilize hessian

tolerance

A small numeric scalar giving the convergence criterion

iter.max

Maximum number of iterations

halving.max

Maximum number of step-halfing

relative

A logical scalar indicating if relative convergence should be checked.

return.hessian

A logical scalar indicating if the final Hessian matrix is returned.

debugging

A logical scalar indicating if the debuggging mode of the code should be run.

Value

A numeric vector of updated parameters, with attributes

'objective'

The final evaluated objective function

'gradient'

The final gradient vector

'iter'

The number of iterations

'hessian'

The final Hessian matrix, only available if return.hessian=TRUE.

References

Long Qu, Dan Nettleton, Jack Dekkers (2012) A hierarchical semiparametric model for incorporating inter-gene relationship information for analysis of genomic data. Biometrics, 68(4):1168-1177

See Also

penLik.EMNewton, EMupdate