Local likelihood modeling by adaptive weights smoothing
- Polzehl, Jörg
- Spokoiny, Vladimir
2010 Mathematics Subject Classification
- adaptive weights, local likelihood, exponential family, density estimation, volatility, tail index, classification
The paper presents a unified approach to local likelihood estimation for a broad class of nonparametric models, including e.g. the regression, density, Poisson and binary response model. The method extends the adaptive weights smoothing (AWS) procedure introduced in Polzehl and Spokoiny (2000) in context of image denoising. Performance of the proposed procedure is illustrated by a number of numerical examples and applications to estimation of the tail index parameter, classification, density and volatility estimation.
- Probab. Theory Related Fields, 135 (2006) pp. 335--362.