B ¤ŠãZã@sldZddlmZddlmZddlZddlmZddl m Z ddl m Z Gd d „d eƒZ Gd d „d e ƒZdS) zÿ This script contains empirical likelihood ANOVA. Currently the script only contains one feature that allows the user to compare means of multiple groups General References ------------------ Owen, A. B. (2001). Empirical Likelihood. Chapman and Hall. é)Údivision)ÚrangeNé)Ú _OptFuncts)Úoptimize)Úchi2c@seZdZdZdd„ZdS)Ú _ANOVAOptzX Class containing functions that are optimized over when conducting ANOVA cCsÞ|j}|j}|j}t ||f¡}d}x@tt|ƒƒD]0}|t||ƒ}||||||…|f<|}q2W|} t | jd¡d| jd} |  t |¡| | ¡} dt  | | j ¡} d|d| |_ t  t ||j ¡¡} d| S)a4 Optimizes the likelihood under the null hypothesis that all groups have mean mu Parameters ---------- mu : float The common mean Returns ------- llr : float -2 times the llr ratio, which is the test statistic rgð?éþÿÿÿ)ÚnobsÚendogÚ num_groupsÚnpZzerosrÚlenZonesÚshapeZ _modif_newtonÚdotÚTÚ new_weightsÚsumÚlog)ÚselfÚmur r r Z endog_asarrayZobs_numZarr_numZ new_obs_numZest_vectZwtsZeta_starZdenomÚllr©rú:lib/python3.7/site-packages/statsmodels/emplike/elanova.pyÚ_opt_common_mus"z_ANOVAOpt._opt_common_muN)Ú__name__Ú __module__Ú __qualname__Ú__doc__rrrrrrsrc@s"eZdZdZdd„Zddd„ZdS) ÚANOVAzë A class for ANOVA and comparing means. Parameters ---------- endog : list of arrays endog should be a list containing 1 dimensional arrays. Each array is the data collected from a certain group. cCs<||_t|jƒ|_d|_x|jD]}|jt|ƒ|_q WdS)Nr)r rr r )rr ÚirrrÚ__init__Js   zANOVA.__init__NrcCs¤|dk rF| |¡}dt ||jd¡}|r:||||jfS|||fSnZtj|j|ddd}|d}t|dƒ}dt ||jd¡}|r–||||jfS|||fSdS)a& Returns -2 log likelihood, the pvalue and the maximum likelihood estimate for a common mean. Parameters ---------- mu : float If a mu is specified, ANOVA is conducted with mu as the common mean. Otherwise, the common mean is the maximum empirical likelihood estimate of the common mean. Default is None. mu_start : float Starting value for commean mean if specific mu is not specified. Default = 0 return_weights : bool if TRUE, returns the weights on observations that maximize the likelihood. Default is FALSE Returns ------- res: tuple The log-likelihood, p-value and estimate for the common mean. NrF)Z full_outputZdispr)rrZcdfr rrZ fmin_powellÚfloat)rrZmu_startZreturn_weightsrZpvalZresZ mu_commonrrrÚ compute_ANOVAQs     zANOVA.compute_ANOVA)Nrr)rrrrr!r#rrrrr>s r)rZ __future__rZstatsmodels.compat.pythonrZnumpyr Z descriptiverZscipyrZ scipy.statsrrrrrrrÚ s     )