{"ID":28583,"CreatedAt":"2026-02-27T13:00:40Z","UpdatedAt":"2026-02-27T13:00:40Z","DeletedAt":null,"paper_url":"https://paperswithcode.com/paper/a-bayesian-approach-to-type-specific-conic","arxiv_id":"1611.06296","title":"A Bayesian approach to type-specific conic fitting","abstract":"A perturbative approach is used to quantify the effect of noise in data\npoints on fitted parameters in a general homogeneous linear model, and the\nresults applied to the case of conic sections. There is an optimal choice of\nnormalisation that minimises bias, and iteration with the correct reweighting\nsignificantly improves statistical reliability. By conditioning on an\nappropriate prior, an unbiased type-specific fit can be obtained. Error\nestimates for the conic coefficients may also be used to obtain both bias\ncorrections and confidence intervals for other curve parameters.","url_abs":"http://arxiv.org/abs/1611.06296v1","url_pdf":"http://arxiv.org/pdf/1611.06296v1.pdf","authors":"[\"Matthew Collett\"]","published":"2016-11-19T00:00:00Z","tasks":"[\"Vocal Bursts Type Prediction\"]","methods":"[]","has_code":false}