M/Ph?*ddlZddlmZmZmZmZmZmZmZm Z ddl m Z ddZ e dkrejgdZejdd gZe eed Zejgd Zejeed ejgd dzZejgdZe eed ZejgdZdS)N)doteye diag_indiceszerosonesdiagasarrayr_)solveaqc t|}|jdkr |dddf}t|}|jdkr |dddf}t|}t|}|dkrd}nH|dkrd}n?|dkr'|d}|st d nt d |z||z}||kr||z }nd }t jt j|t|df} td | d|z } t|} t|\} } | | dd | dd fxxdz cc<d | | dd dz| dd f<d | | dd | dd dzf<tt| | | }t||z||zf}||d|d|f<| |d||df<| j||dd|f<t||zdf}||| d<t||}|d| }|d kr3||dz ||dz z }|||dz}t ||f}| S)a Modified Denton's method to convert low-frequency to high-frequency data. Uses proportionate first-differences as the penalty function. See notes. Parameters ---------- indicator : array_like A low-frequency indicator series. It is assumed that there are no pre-sample indicators. Ie., the first indicators line up with the first benchmark. benchmark : array_like The higher frequency benchmark. A 1d or 2d data series in columns. If 2d, then M series are assumed. freq : str {"aq","qm", "other"} The frequency to use in the conversion. * "aq" - Benchmarking an annual series to quarterly. * "mq" - Benchmarking a quarterly series to monthly. * "other" - Custom stride. A kwarg, k, must be supplied. **kwargs Additional keyword argument. For example: * k, an int, the number of high-frequency observations that sum to make an aggregate low-frequency observation. `k` is used with `freq` == "other". Returns ------- transformed : ndarray The transformed series. Examples -------- >>> indicator = [50,100,150,100] * 5 >>> benchmark = [500,400,300,400,500] >>> benchmarked = dentonm(indicator, benchmark, freq="aq") Notes ----- Denton's method minimizes the distance given by the penalty function, in a least squares sense, between the unknown benchmarked series and the indicator series subject to the condition that the sum of the benchmarked series is equal to the benchmark. The modification allows that the first value not be pre-determined as is the case with Denton's original method. If the there is no benchmark provided for the last few indicator observations, then extrapolation is performed using the last benchmark-indicator ratio of the previous period. Minimizes sum((X[t]/I[t] - X[t-1]/I[t-1])**2) s.t. sum(X) = A, for each period. Where X is the benchmarked series, I is the indicator, and A is the benchmark. References ---------- Bloem, A.M, Dippelsman, R.J. and Maehle, N.O. 2001 Quarterly National Accounts Manual--Concepts, Data Sources, and Compilation. IMF. http://www.imf.org/external/pubs/ft/qna/2000/Textbook/index.htm Cholette, P. 1988. "Benchmarking systems of socio-economic time series." Statistics Canada, Time Series Research and Analysis Division, Working Paper No TSRA-88-017E. Denton, F.T. 1971. "Adjustment of monthly or quarterly series to annual totals: an approach based on quadratic minimization." Journal of the American Statistical Association. 99-102. Nr qmotherkz$k must be supplied with freq="other"zfreq %s not understoodrg?)r ndimlenget ValueErrornpkronrrrsqueezerrrTr r ) indicator benchmarkfreqkwargsNmrnqBZinvHTH diag_idx0 diag_idx1WIAXbi extrapolateds ]/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/statsmodels/tsa/interp/denton.pydentonmr1Vs` ""I~aaaf%  ""I~aaaf%  IA IA t||     JJsOO GEFF F G1D8999 !A1uu E  q 41;;''A 9$$&&rr** + +D a&&C'??Iy !B$1R4()))Q.))),.C #2#q)CRC.(),.C #2# #2#q(() CSMM$A qsAaCjAAbqb!eHAbqbeHsAabb!eH qs1gA AqbccF a A #A2#A 1uu qsVIacN "IabbM) q~  99;;__main__) ǧX@333333Y@ǧY@r4gX@gffffffY@g̬Y@`Y@g Y@gY@gY@r5g@@gfffffA@)r) gfffffN@g333333@gfffffҏ@g33333@gy@gK@g33333@l@gfffffB@g@g̾@r6r)2dr8)i,r<r;)g93LmP@g _@g|\zg@gض(A^@g4-HL@g׆q~Z@g pb@g `}V@gT FD@gxeR@gj[@g`*S@g?ZaE@gEbW@g7XO-c@gw#k[@g 7%M@gk, ^@g89@g@gQHm`@)r )numpyrrrrrrrr r numpy.linalgr r1__name__arrayrrx_imf imf_statatestingassert_almost_equalzQYx_dentonx_statar2r0rJsdXXXXv z DDDEEI%((I GIyt 4 4 4EPPPQQIJ""9eQ777 """Q& ' 'B&&&''Awr14(((HbhGGGHHG --r2