arXiv Open Access 2016

A Bayesian approach to type-specific conic fitting

Matthew Collett
Lihat Sumber

Abstrak

A perturbative approach is used to quantify the effect of noise in data points on fitted parameters in a general homogeneous linear model, and the results applied to the case of conic sections. There is an optimal choice of normalisation that minimises bias, and iteration with the correct reweighting significantly improves statistical reliability. By conditioning on an appropriate prior, an unbiased type-specific fit can be obtained. Error estimates for the conic coefficients may also be used to obtain both bias corrections and confidence intervals for other curve parameters.

Topik & Kata Kunci

Penulis (1)

M

Matthew Collett

Format Sitasi

Collett, M. (2016). A Bayesian approach to type-specific conic fitting. https://arxiv.org/abs/1611.06296

Akses Cepat

Lihat di Sumber
Informasi Jurnal
Tahun Terbit
2016
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓