U Kv fZã@sTdZddlZddlmZddlmZddlmZGdd„deƒZ Gd d „d e ƒZ dS) a 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. éNé)Ú _OptFuncts)Úoptimize)Úchi2c@seZdZdZdd„ZdS)Ú _ANOVAOptzX Class containing functions that are optimized over when conducting ANOVA. cCsÚ|j}|j}|j}t ||f¡}d}tt|ƒƒD]0}|t||ƒ}||||||…|f<|}q0|} t | jd¡d| jd} |  t |¡| | ¡} dt  | | j ¡} d|d| |_ t  t ||j ¡¡} d| S)a7 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_groupsÚnpÚzerosÚrangeÚlenZonesÚshapeZ _modif_newtonÚdotÚTÚ new_weightsÚsumÚlog)ÚselfÚmurr r Z endog_asarrayZobs_numZarr_numZ new_obs_numZest_vectZwtsZeta_starZdenomÚllr©rú?/tmp/pip-unpacked-wheel-2v6byqio/statsmodels/emplike/elanova.pyÚ_opt_common_mus$ÿz_ANOVAOpt._opt_common_muN)Ú__name__Ú __module__Ú __qualname__Ú__doc__rrrrrrsrc@s"eZdZdZdd„Zddd„ZdS) ÚANOVAzë A class for ANOVA and comparing means. Parameters ---------- endog : list of arrays endog should be a list containing 1 dimensional arrays. Each array is the data collected from a certain group. cCs8||_t|jƒ|_d|_|jD]}|jt|ƒ|_qdS)Nr)r rr r)rr ÚirrrÚ__init__Fs   zANOVA.__init__NrcCsª|dk rF| |¡}dt ||jd¡}|r:||||jfS|||fSn`tj|j|ddd}|d}tt  |d¡ƒ}dt ||jd¡}|rœ||||jfS|||fSdS)a( Returns -2 log likelihood, the pvalue and the maximum likelihood estimate for a common mean. Parameters ---------- mu : float If a mu is specified, ANOVA is conducted with mu as the common mean. Otherwise, the common mean is the maximum empirical likelihood estimate of the common mean. Default is None. mu_start : float Starting value for commean mean if specific mu is not specified. Default = 0. return_weights : bool if TRUE, returns the weights on observations that maximize the likelihood. Default is FALSE. Returns ------- res: tuple The log-likelihood, p-value and estimate for the common mean. NrF)Z full_outputZdispr) rrZcdfr rrZ fmin_powellÚfloatr Zsqueeze)rrZmu_startZreturn_weightsrZpvalÚresZ mu_commonrrrÚ compute_ANOVAMs    ÿzANOVA.compute_ANOVA)Nrr)rrrrr!r$rrrrr:s r) rZnumpyr Z descriptiverZscipyrZ scipy.statsrrrrrrrÚs     (