B ¤ŠãZM ã@sddZddlmZddlZddlmZddlmZm Z ddlm Z ddlm Z d Z Gd d „d eƒZ dS) z7Multivariate analysis of variance author: Yichuan Liu é)ÚdivisionN)ÚModelé)Ú_multivariate_ols_testÚ_hypotheses_doc)Ú_multivariate_ols_fit)ÚMultivariateTestResultszrestructuredtext encs:eZdZdZd ‡fdd„ Zd dd„Zded e_‡ZS) ÚMANOVAa6 Multivariate analysis of variance The implementation of MANOVA is based on multivariate regression and does not assume that the explanatory variables are categorical. Any type of variables as in regression is allowed. Parameters ---------- endog : array_like Dependent variables. A nobs x k_endog array where nobs is the number of observations and k_endog is the number of dependent variables. exog : array_like Independent variables. A nobs x k_exog array where nobs is the number of observations and k_exog is the number of independent variables. An intercept is not included by default and should be added by the user. Models specified using a formula include an intercept by default. Attributes ---------- endog : array See Parameters. exog : array See Parameters. References ---------- .. [*] ftp://public.dhe.ibm.com/software/analytics/spss/documentation/statistics/20.0/en/client/Manuals/IBM_SPSS_Statistics_Algorithms.pdf ÚnoneNc sXt|jƒdks|jddkr$tdƒ‚tt|ƒj||f||dœ|—Žt|j|jƒ|_ dS)Nrz=There must be more than one dependent variable to fit MANOVA!)ÚmissingÚhasconst) ÚlenÚshapeÚ ValueErrorÚsuperr Ú__init__rÚendogÚexogÚ _fittedmod)Úselfrrr r Úkwargs)Ú __class__©ú>lib/python3.7/site-packages/statsmodels/multivariate/manova.pyr0s zMANOVA.__init__c Csð|dkrÌt|dƒrx|jdk rxt|jdƒrx|jjj}g}x”|D]6}t |jjd¡||dd…f}| ||dg¡qs