[R-sig-Geo] variogram question

[G. Allegri]

I forgot to add another important class of model parameters
estimators: maximum a posteriori (MAP)

2008/8/21 Pilar Tugores Ferra <Pilar.Tugores at ba.ieo.es>:
>
> I would add Ordinary Least Squares (It may be the same as your SS), Weighted Least Squares, Maximum Likelihood and Restricted Maximum Likelihood.
> These four methods are available in the function likfit of the package geoR.
> I've been using it a little bit and I think sometimes one method works better than the other one but I don't know the clues for making an a priori decision!
>
>
> Mª Pilar Tugores Ferrà
>
> Becaria FPI - PhD Student
>
> Acústica de Pesquerías
>
> I.E.O. - Centro Oceanográfico de Baleares
>
> Muelle de Poniente s/n
>
> 07015 Palma de Mallorca (España)
>
> Tel.: (34) 971 401561
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>
> -----Mensaje original-----
> De: r-sig-geo-bounces at stat.math.ethz.ch [mailto:r-sig-geo-bounces at stat.math.ethz.ch] En nombre de G. Allegri
> Enviado el: 21 August 2008 00:09
> Para: Paul Hiemstra
> CC: r-sig-geo at stat.math.ethz.ch
> Asunto: Re: [R-sig-Geo] variogram question
>
>> You spoke of more sophisticated methods of automatically choosing between models, what kind of methods did you have in mind?
>
> Here's a list I gathered some time ago. Many of them are just buzzwords form me!
>
> ‧ Adjusted R-squared (Wherry 1931)
> ‧ Bootstrap (Efron 1979)
> ‧ Cross-validation (Stone 1974; Geisser 1975)
>    – Generalized cross-validation (GCV) (Craven and Wahba 1979)
>    – k-fold cross-validation
>    – Leave-one-out cross-validation
> ‧ Jacknife
> ‧ Linear regression
> ‧ Shibata's model selector (sms) (Shibata 1981)
> ‧ Signal-to-noise ratio
> ‧ Test set validation
> ‧ Akaike information criterion (AIC)
>   – AIC (Akaike 1973)
>   – AICc (Hurvich and Tsai 1989)
>   – QAIC (Lebreton, et al. 1992)
>   – QAICc (Lebreton, et al. 1992)
>   – AICW (Wilks 1995)
> ‧ CAT (Parzen 1974, 1977)
> ‧ CP (Mallow's Cp) (Mallows 1973)
> ‧ Deviance information criterion (DIC) (Spiegelhalter, et al. 2002)
> ‧ FIC (Wei 1992)
> ‧ Final prediction error (FPE) (Akaike 1969)
> ‧ FPEα (Bhansali and Downham 1977)
> ‧ FPEC (de Luna 1998)
> ‧ FPER (Larsen and Hansen 1994)
> ‧ GM (Geweke and Meese 1981)
> ‧ Generalized prediction error (GPE) (Moody 1991, 1992)
> ‧ Hannan and Quinn Criterion (HQ) (Hannan and Quinn 1979)
> ‧ KIC (Cavanaugh 1999)
> ‧ KICc (Cavanaugh 2004)
> ‧ Minimum description length (MDL) (Rissanen 1978)
> ‧ Minimum message length (MML) (Wallace and Boulton 1968)
> ‧ Predicted squared error (PSE) (Barron 1984)
> ‧ PRESS (Allen 1974)
> ‧ Schwarz criterion (also Schwarz information criterion (SIC) or
> Bayesian information criterion (BIC) or Schwarz-Bayesian information
> criterion) (Schwarz 1978)
> ‧ Structural risk minimization (SRM) (Vapnik and Chervonenkis 1974)
> ‧ TIC (Takeuchi's information criterion) (Takeuchi 1976)
> ‧ VC-dimension (Vapnik and Chervonekis 1968, 1971; Vapnik 1979)
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