Asymptotic theory for description of regions in which Newton-Raphson iterations converge to location M-estimators

B.R. Clarke

doi:10.1016/0378-3758(86)90086-8

Back

Asymptotic theory for description of regions in which Newton-Raphson iterations converge to location M-estimators

Journal article

Peer reviewed

Asymptotic theory for description of regions in which Newton-Raphson iterations converge to location M-estimators

B.R. Clarke

Journal of Statistical Planning and Inference, Vol.15(C), pp.71-85

1986

DOI: https://doi.org/10.1016/0378-3758(86)90086-8

Files and links (1)

url

Link to Published Version *Subscription may be requiredView

Abstract

By examination of properties of the function of the sample and location parameter that describes the M-estimating equation for location a detailed probabilistic description of regions from which the Newton-Raphson algorithm converges to the location M-estimator is given. In finite samples an asymptotic distribution can be used to approximate the size of the region from which convergence occurs. This gives experimenters an idea of the tolerance acceptable for an initial estimate to begin an iteration. Empirical evidence is given which highlights the results.

Details

Title: Asymptotic theory for description of regions in which Newton-Raphson iterations converge to location M-estimators
Authors/Creators: B.R. Clarke (Author/Creator)
Publication Details: Journal of Statistical Planning and Inference, Vol.15(C), pp.71-85
Publisher: Elsevier BV
Identifiers: 991005540318107891
Murdoch Affiliation: School of Chemical and Mathematical Science
Language: English
Resource Type: Journal article

Metrics

50 Record Views