Terhi Mäkinen & Lasse Holmström (2017) Modeling probability density through ultraspherical polynomial transformations, Communications in Statistics - Simulation and Computation, 46:8, 5879-5900, DOI: 10.1080/03610918.2016.1186181
Modeling probability density through ultraspherical polynomial transformations
|Author:||Mäkinen, Terhi1; Holmström, Lasse2|
1Finnish Meteorological Institute, Helsinki, Finland
2Department of Mathematical Sciences, University of Oulu, Oulu, Finland
|Online Access:||PDF Full Text (PDF, 0.4 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2017112050793
|Publish Date:|| 2017-11-20
We present a method for fitting parametric probability density models using an integrated square error criterion on a continuum of weighted Lebesgue spaces formed by ultraspherical polynomials. This approach is inherently suitable for creating mixture model representations of complex distributions and allows fully autonomous cluster analysis of high-dimensional datasets. The method is also suitable for extremely large sets, allowing post facto model selection and analysis even in the absence of the original data. Furthermore, the fitting procedure only requires the parametric model to be pointwise evaluable, making it trivial to fit user-defined models through a generic algorithm.
Communications in statistics. B, Simulation and computation
|Pages:||5879 - 5900|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
112 Statistics and probability
Work of LH supported by grant no. 24301034 from the Academy of Finland.
|Academy of Finland Grant Number:||
250862 (Academy of Finland Funding decision)
This is an Accepted Manuscript of an article published by Taylor & Francis in Communications in statistics: simulation and computation on 27 May 2016, available online: http://www.tandfonline.com/10.1080/03610918.2016.1186181.