Posts tagged ‘AIC’

[ArXiv] 3rd week, Jan. 2008

Seven preprints were chosen this week and two mentioned model selection. Continue reading ‘[ArXiv] 3rd week, Jan. 2008’ »

[ArXiv] 2nd week, Jan. 2007

It is notable that there’s an astronomy paper contains AIC, BIC, and Bayesian evidence in the title. The topic of the paper, unexceptionally, is cosmology like other astronomy papers discussed these (statistical) information criteria (I only found a couple of papers on model selection applied to astronomical data analysis without articulating CMB stuffs. Note that I exclude Bayes factor for the model selection purpose).

To find the paper or other interesting ones, click Continue reading ‘[ArXiv] 2nd week, Jan. 2007’ »

Cross-validation for model selection

One of the most frequently cited papers in model selection would be An Asymptotic Equivalence of Choice of Model by Cross-Validation and Akaike’s Criterion by M. Stone, Journal of the Royal Statistical Society. Series B (Methodological), Vol. 39, No. 1 (1977), pp. 44-47.
(Akaike’s 1974 paper, introducing Akaike Information Criterion (AIC), is the most often cited paper in the subject of model selection).
Continue reading ‘Cross-validation for model selection’ »

[ArXiv] Kernel Regression, June 20, 2007

One of the papers from arxiv/astro-ph discusses kernel regression and model selection to determine photometric redshifts astro-ph/0706.2704. This paper presents their studies on choosing bandwidth of kernels via 10 fold cross-validation, choosing appropriate models from various combination of input parameters through estimating root mean square error and AIC, and evaluating their kernel regression to other regression and classification methods with root mean square errors from literature survey. They made a conclusion of flexibility in kernel regression particularly for data at high z.
Continue reading ‘[ArXiv] Kernel Regression, June 20, 2007’ »