B ¤ŠãZµã@srdZddlZddlmZejZejZej Z ddl m Z Gdd„de ƒZ ddlmZddlmZGd d „d eƒZdS) aÝLinear Model with Student-t distributed errors Because the t distribution has fatter tails than the normal distribution, it can be used to model observations with heavier tails and observations that have some outliers. For the latter case, the t-distribution provides more robust estimators for mean or mean parameters (what about var?). References ---------- Kenneth L. Lange, Roderick J. A. Little, Jeremy M. G. Taylor (1989) Robust Statistical Modeling Using the t Distribution Journal of the American Statistical Association Vol. 84, No. 408 (Dec., 1989), pp. 881-896 Published by: American Statistical Association Stable URL: http://www.jstor.org/stable/2290063 not read yet Created on 2010-09-24 Author: josef-pktd License: BSD TODO ---- * add starting values based on OLS * bugs: store_params doesn't seem to be defined, I think this was a module global for debugging - commented out * parameter restriction: check whether version with some fixed parameters works éN)Úspecial)ÚGenericLikelihoodModelcsDeZdZdZ‡fdd„Zddd„Zdd „Zd d „Zdd d „Z‡Z S)Ú TLinearModela?Maximum Likelihood Estimation of Linear Model with t-distributed errors This is an example for generic MLE. Except for defining the negative log-likelihood method, all methods and results are generic. Gradients and Hessian and all resulting statistics are based on numerical differentiation. csÄ|jjd|_t|dƒsd|_|jdkrPd|_d|_|jjdd|_ddg}nP|jjdd|_tj t  |jjdd¡}|j|d<||_t  |¡|_dg}|  |¡|  ¡tt|ƒ ¡dS)NéÚfix_dfFéÚdfÚscaleéþÿÿÿ)ÚexogÚshapeÚk_varsÚhasattrrÚ fixed_paramsZfixed_paramsmaskÚk_paramsÚnpÚnanZzerosZisnanZ_set_extra_params_namesÚ_set_start_paramsÚsuperrÚ initialize)ÚselfZextra_params_namesZfixdf)Ú __class__©úc  st|\}}|dk r.t|ƒ||dkrNtdƒ‚n t dt ||¡ddgf¡}tt|ƒjf|||||dœ|—Ž} | S)Nrz(start_param need sum(order) + 2 elementsgš™™™™™©?rr)ÚorderrÚmethodÚmaxiterÚtol)ÚlenÚ ValueErrorrZ concatenater rr3Úfit_mle) rr8rr9r:r;ÚkwdsZnarZnmaZres)rrrr>Ôs  z TArma.fit_mle)Nr5r6r7)r-r.r/r0r%r#r>r1rr)rrr3©s r3)r0ZnumpyrZscipyrÚlogr)Zpir*Zgammalnr(Zstatsmodels.base.modelrrr"Zstatsmodels.tsa.arma_mler2r3rrrrÚ"s  w