M/Ph8 D dZddlmZddlZddlmZdgZddlm Z dZ dZ Gd d e Z Gd dZ Gd d e ZGdde ZGdde Zedkr2ddlmcmZddlZddlm Z ddlmZejjZejddZejddZej edee!dZ"ej#e"Z$e$%ddg&Z'eddg(e!)ddZej*edZe edZ+edZ,e eee+e,ddgdZ-e-.d !Z/e-.d"d#$Z0e-.d%d#$Z1e-.d"d&$Z2e-.d%d&$Z3e-.d%d'$Z4ej5gd(Z6e6j7dZ8ej9e6Z:ej5gd)Z;ej9e;Ze;dddfezeCe?zfZEejFeEeEjGe@ejHe8zzZIeJeIeJejKLeIejKMeI\ZNZOejFeOd-eNz eOzjGZPejKQeIZRejFeOeNeOzjGZSeJejTejUeSeIz eJejTejUejFePeIejHe8z eOejAeNz ZVeJejTejUejFeVeVjGePz ej5eBeCe@gZWejXe6e;fZYe eYeW\ZZZ[Z\eJejTejUeZeIz eJejTejUe[ePz eJejTejUe\eVz eejFe>ejKQejFe>jGe>e>jGgZ]ejHe8e]z Z^eJejTejUejFe^e6dSdS).z Sandbox Panel Estimators References ----------- Baltagi, Badi H. `Econometric Analysis of Panel Data.` 4th ed. Wiley, 2008. )reduceN)GLS PanelModel)Panelci}tjt|}tt|D]G}|||vr*|||t|i|||||<H|S)z Returns unique numeric values for groups without sorting. Examples -------- >>> X = np.array(['a','a','b','c','b','c']) >>> group(X) >>> g array([ 0., 0., 1., 2., 1., 2.]) )npzeroslenrangeupdate)X uniq_dictgroupis b/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/statsmodels/sandbox/panel/panelmod.pyrrsI HSVV  E 3q66]]##ty    adS^^4 5 5 5QqT?a Lc0|jdkr |dddf}|j\}}|dtj|z}t |D]k}|dd||dzf}tj|}||||ktz}|tj||j z }ltj |\} } tj| d| z | zj } | tj | z } || | fS)aGcalculate error covariance matrix for random effects model Parameters ---------- groups : ndarray, (nobs, nre) or (nobs,) array of group/category observations sigma : ndarray, (nre+1,) array of standard deviations of random effects, last element is the standard deviation of the idiosyncratic error Returns ------- omega : ndarray, (nobs, nobs) covariance matrix of error omegainv : ndarray, (nobs, nobs) inverse covariance matrix of error omegainvsqrt : ndarray, (nobs, nobs) squareroot inverse covariance matrix of error such that omega = omegainvsqrt * omegainvsqrt.T Notes ----- This does not use sparse matrices and constructs nobs by nobs matrices. Also, omegainvsqrt is not sparse, i.e. elements are non-zero N) ndimshapereyer uniqueastypefloatdotTlinalgeighsqrt) groupssigmasnobsnreomegaigrr groupuniqdummygrevevecomegainv omegainvhalfs r repanel_covr-'s 8{a$ ID# 2Jrvd|| #ESzz--qqqSU{#Ie$$ +)!3 ; ;E B BB "&'),,,y~~e$$HBvdQrTD[O,,H #L (L ((rceZdZdS) PanelDataN__name__ __module__ __qualname__rrr/r/SDrr/cFeZdZdZ d dZdZdZd dZdd Zd Z d Z dS)ra An abstract statistical model class for panel (longitudinal) datasets. Parameters ---------- endog : array_like or str If a pandas object is used then endog should be the name of the endogenous variable as a string. # exog # panel_arr # time_arr panel_data : pandas.Panel object Notes ----- If a pandas object is supplied it is assumed that the major_axis is time and that the minor_axis has the panel variable. NcB||||||||dSdSN) initialize)selfendogexogpaneltimextnamesequation panel_datas r__init__zPanelModel.__init__is4   OOE4gx H H H H H  rc|d}|d|_|dd}|d|_|d|_|ddk} d| vr:t j| dkdd} || d| |_||_ t j t j ||_ t j |}||_ t j ||_t j ||_t j||_t j||_dS)zG Initialize plain array model. See PanelModel  rrNTcons)split endog_name panel_name time_namevarrwhereinsert _cons_index exog_namessqueezeasarrayr;r<r=r>r paneluniqtimeuniq) r:r;r<r=r>r?r@namesrNnovar cons_indexs rr9zPanelModel.initializezss##(122Y !!*  q  5==%1*--a03J   j& 1 1 1 $Z 5 1 122 z$ Z&& Jt$$ 5)) $ rcJ||_||j}tj||_|.|j}||||j|_ ||_ ||_ |j |_ |j|_dSr8)rAvaluesrrOr;columnstolistremove filterItemsr< _exog_name _endog_name major_axis _timeseries minor_axis _panelseries)r:rArG exog_namer;s rinitialize_pandaszPanelModel.initialize_pandass$:&-Z&&  "*1133I   Z ( ( (**955< #%%0&1ronewayFc |dkr|j}|j}n'|dkr|j}|j}nt d|zt |||dddft |t |t |dddf|||dddfkt}|j dkr6tj ||| ddddfz }n+tj ||| dz }|dur|dur|S|dur|dur|| dfS|dur|dur|| d|fS|dur|dur||fSdSdS)z[ Get group means of X by time or by panel. index default is panel rdr>zindex %s not understoodNrFT) r=rQr>rR ValueErrorprintr rrrrrsum) r:r indexcountsdummiesYuniqdummymeans r _group_meanzPanelModel._group_means H   A>DD f__ A=DD6>?? ? atAAAdF|SVVSYYD4L8I8I   d111T6l"**511 6A::6%??599Q<<$#77DD6%??599Q<</D U??w%//K t^^5 0 01% % t^^41u, , u__D; _rc^|r|}|}|r|dvrtd|z|dkr,t|j|jS|dkr|||S|dkr|||SdS)ab method : LSDV, demeaned, MLE, GLS, BE, FE, optional model : between fixed random pooled [gmm] effects : oneway time twoway femethod : demeaned (only one implemented) WLS remethod : swar - amemiya nerlove walhus Notes ----- This is unfinished. None of the method arguments work yet. Only oneway effects should work. )lsdvdemeanedmleglsbefez%s not a valid methodpooledbetweenfixedN)lowerrfrr;r<fit _fit_btwn _fit_fixed)r:modelmethodeffectss rr|zPanelModel.fits6  $\\^^F   ?f%8884v=>> > H  tz49--1133 3 I  >>&'22 2 G  ??6733 3  rc|dkr9||j|}||j|}ntd|zt ||}|S)Ntwowayriz1%s effects is not valid for the between estimator)rpr;r<rfrr|)r:rrr;r<befits rr}zPanelModel._fit_btwns h  $$TZw$??E##DIW#==DD)+2344 4E4  $$&& rc|j}|j}d}|dvr|dkrd}d}|||d\}}|||}|t}|t j||z }|t j||d z }|s|d krg||d d \}} ||d }|t j|| z }|t j| j|z }t||dd|j f } | S) NF)rdtwowaysrTrd)rirjrr)axisr>)rirk) r;r<rprintrrepeatrrrrMr|) r:rrr;r< demeantwice endog_meanrj exog_meanrkfefits rr~zPanelModel._fit_fixed)sh y * * *)##" "!%!1!1%w"2"" J((W(==I]]3''FBIj&999E")IvA>>>>D  7'V++"&"2"25#3## J((V(<r)rrrrrrrr)rrrrrrrrg?g@g@r)_r functoolsrnumpyr#statsmodels.regression.linear_modelr__all__pandasrrr-r/rrrrr1numpy.lib.recfunctionslib recfunctionsnprfstatsmodels.apiapismdatasetsgrunfeldloaddatar;r<fullexog append_fieldsr panel_arr DataFramepanel_df set_indexto_panel panel_pandaviewreshape add_constantr=r panel_modr| panel_olspanel_bepanel_fe panel_bet panel_fet panel_fe2arrayr!rr#rr'periods perioduniqrr(dummypesigmar sigmagrsigmapec_dummyallrrrr%rgrcholeskyrr)r*r+inv omegainv2 omegacompmaxabsr,sigmas2 column_stackgroups2omega_ omegainv_ omegainvhalf_PgrQgrr4rrrs333333 .&()()()X        jjjjjjjj^     z        z        :    z)))))))))MMM      ;  $ $ & &D Jtt Ey#H""8\5%I v **H$$ff%566??AAK WY' ( - -e 4 4 < >I GV < >E E%LLL E")  U # #$$$y~~e$$HBrvdQrTD[O,,H e$$Itb4i]++I E&"& E)** + +,,, E&"&x..=>> ? ?@@@ #L E&"&|LN;;hFGG H HIIIbh%011Gbovw/00G'2{7G'D'D$FI} E&"&'' ( ())) E&"& H,-- . ./// E&"& 455 6 6777 & IMM&"&G44 5 5giA B BC "&,, C E&"&sF++,, - -.....Wr