!g6@jdZddlmZddlmZddlZdZGddejZ dZ d \Z Z d \Z Z d Z d Zd Ze ej e eddddZe ej ej$ej&ddddZe ej*ej&ej$dZ GddejZGddejZdZ GddejZGdd ZeZeej ej:ej<ej>ej@ejBd!d"ejDdd#d$% Z#eejHej:ej<ej>ej@ejBd!d"ejDdd#d&% Z%d'Zd(Zd)Z d*Z!d+Z&eej e&eee e!d,ejD d"dd-d.% Z'd/Zd0Zd1Z d2Z!d3Z(eej ejReee e!d!d"ejDdd4d5% Z*y)6a{ A class for the distribution of a non-linear monotonic transformation of a continuous random variable simplest usage: example: create log-gamma distribution, i.e. y = log(x), where x is gamma distributed (also available in scipy.stats) loggammaexpg = Transf_gen(stats.gamma, np.log, np.exp) example: what is the distribution of the discount factor y=1/(1+x) where interest rate x is normally distributed with N(mux,stdx**2)')? (just to come up with a story that implies a nice transformation) invnormalg = Transf_gen(stats.norm, inversew, inversew_inv, decr=True, a=-np.inf) This class does not work well for distributions with difficult shapes, e.g. 1/x where x is standard normal, because of the singularity and jump at zero. Note: I'm working from my version of scipy.stats.distribution. But this script runs under scipy 0.6.0 (checked with numpy: 1.2.0rc2 and python 2.4) This is not yet thoroughly tested, polished or optimized TODO: * numargs handling is not yet working properly, numargs needs to be specified (default = 0 or 1) * feeding args and kwargs to underlying distribution is untested and incomplete * distinguish args and kwargs for the transformed and the underlying distribution - currently all args and no kwargs are transmitted to underlying distribution - loc and scale only work for transformed, but not for underlying distribution - possible to separate args for transformation and underlying distribution parameters * add _rvs as method, will be faster in many cases Created on Tuesday, October 28, 2008, 12:40:37 PM Author: josef-pktd License: BSD )stats) distributionsNc |jDcic]*\}}|jdr|jddd|,}}}|jdd}||fScc}}w)Nu_u_args)items startswithreplacepop)kwargskvu_kwargsr s j/var/www/dash_apps/app1/venv/lib/python3.12/site-packages/statsmodels/sandbox/distributions/transformed.pyget_u_argskwargsr,sf6t>v>? ?99]TXX]]1q5B4B6BC Cr-__name__ __module__ __qualname____doc__r)r1r5 __classcell__r,s@rrr4s 6IDr-rc.tjd|Sr/)r%divider3s rinverserAcs 99S! r-)g?g?)g"@r0c.ddtz|tzzz S)Nr0rmuxstdxr@s rinversewrFks !c'AH$ %%r-c.d|z dz tz tz Sr/rCr@s r inversew_invrHos !GcMC 4 ''r-c|SNr"r@s ridentitrKs Hr-Tdiscfznormal-based discount factor)rrrrlnnormzExp transformed normal)rrrrr)rc.eZdZdZfdZdZdZxZS) ExpTransf_genDistribution based on log/exp transformation the constructor can be called with a distribution class and generates the distribution of the transformed random variable cd|vr |d|_nd|_d|vr|d}nd}d|vr|d}nd}t| ||||_yNrrrzLog transformed distributionrrrrrr(r)r'r*r'r+rrrr,s rr)zExpTransf_gen.__init__sd  !),DLDL V &>D1D &=s AA 14(r-cb|jjtj|g|SrJ)r'r1r%logr*r3r+s rr1zExpTransf_gen._cdf$txx}}RVVAY...r-cbtj|jj|g|SrJ)r%expr'r5r*r6r+s rr5zExpTransf_gen._ppf%vvmdhhmmA--..r-r7r=s@rrQrQs&//r-rQc.eZdZdZfdZdZdZxZS) LogTransf_genrRcd|vr |d|_nd|_d|vr|d}nd}d|vr|d}nd}t| ||||_yrTrVrWs rr)zLogTransf_gen.__init__sb  !),DLDL V &>D1D &=s AA 14(r-cb|jjtj|g|SrJ)r'r1r%r]rZs rr1zLogTransf_gen._cdfr[r-cbtj|jj|g|SrJ)r%rYr'r5r^s rr5zLogTransf_gen._ppfr_r-r7r=s@rraras$//r-rac tdttjdd}t|j dttj j ddt|jttj jdt|j dtdttj}t|jdd ttjj dd t|jd d ttjj d d td ttj}t|jd d ttjj d d ttj}t|jd d y) NzResults for lognormalrzLog transformed normal generalrUr)sizezResults for expgamma rNzResults for loglaplace) printrQrnormcdflognormrvsragammar1loggammalaplace loglaplace) lognormalg loggammaexpg loglaplacegloglaplaceexpgs rexamples_transfrwsf !"uzzQ5UVJ *..  %--  Aq !" *    %--  a ! *..a. ! ! -L ,  Ar "# %..  Q #$ ,  Ar "# %..  Q #$  "# .K +  1b !" %    q" %&"5==1N .  a $%r-c@eZdZdZfdZdZdZdZdZdZ xZ S) TransfTwo_genaODistribution based on a non-monotonic (u- or hump-shaped transformation) the constructor can be called with a distribution class, and functions that define the non-linear transformation. and generates the distribution of the transformed random variable Note: the transformation, it's inverse and derivatives need to be fully specified: func, funcinvplus, funcinvminus, derivplus, derivminus. Currently no numerical derivatives or inverse are calculated This can be used to generate distribution instances similar to the distributions in scipy.stats. c||_||_||_||_||_|j dd|_|j dd} |j dd} |j dd} |j dtj } |j d tj} |j d d |_ td i|\|_ |_ ||_ t|=| | | |j | y)NrrrrrrrrrshapeFr r")r# funcinvplus funcinvminus derivplus derivminusr rr%r&r{rr rr'r(r)r!)r*r'r#r|r}r~rr+rrrrrrr,s rr)zTransfTwo_gen.__init__1s  &("$zz)Q/ zz&,/::j*OP::j$/ JJsRVVG $ JJsBFF #ZZ/ &6%?%?" T] 14 X  r-c|j|j_|j|jj|SrJ)_sizer'r#_rvs)r*r+s rrzTransfTwo_gen._rvsPs/yy-..r-cl|jdk(rd}n|jdk(rd}n td||j||jj|j |g|i|z|j ||jj|j|g|i|zz zS)Nurhumpzshape can only be `u` or `hump`)r{ ValueErrorr~r'_pdfr|rr})r*r3r+rsignpdfs rrzTransfTwo_gen._pdfTs :: G ZZ6 !G>? ?$..+mdhhmmD/ H67'r-ryc.eZdZdZdZdZdZdZdZy) SquareFunczclass to hold quadratic function with inverse function and derivative using instance methods instead of class methods, if we want extension to parametrized function c,tj|SrJr%sqrtr*r3s r inversepluszSquareFunc.inverseplusswwqzr-c2dtj|z SNrrs r inverseminuszSquareFunc.inverseminusRWWQZr-c2dtj|z SN?rrs rr~zSquareFunc.derivplusrr-c8ddtj|z z SNrrrrs rrzSquareFunc.derivminussS2771:%%%r-c.tj|dSNrNr%powerrs r squarefunczSquareFunc.squarefuncsxx1~r-N) r8r9r:r;rrr~rrr"r-rrrs    &r-rrr squarenormzsquared normal distribution)r{rrrrrzsquared t distributionc.tj| SrJrr@s rrrs 77A2;r-c4dtj| z Srrr@s rrr ! r-c:ddtj| z z Srrr@s rr~r~s rwwr{" ""r-c4dtj| z Srrr@s rrrrr-c0tj|d Srrr@s r negsquarefuncrs HHQN?r-r negsquarenormz$negative squared normal distributionc|SrJr"r@s rrrrLr-c d|z Srr"r@s rrrs 7Nr-cyr/r"r@s rr~r~s r-cy)Ngr"r@s rrrs r-c,tj|SrJ)r%absr@s rabsfuncrs 66!9r-absnormzabsolute of normal distribution)+r;scipyr scipy.statsrnumpyr%r rv_continuousrrArDrErFrHrKrk invdnormalgr]rYrsrortrQrarwryrsqfuncrrrr~rr& squarenormalgtsquaretgrnegsquarenormalgrr absnormalgr"r-rrsS#H%,D,,,D^  T  T&( X|$!";Y  BFFBFF !QX!9 %++rvvrvvqA  /M// /F/M///D$&R >U'M//U'D. ejj&*;*;V=O=O$1163C3CVEVEV$'3"&&&'lEb  &"3"3V5G5G,,f.>.>@Q@Q"cRVV!"@X #!]K!*JfSV)**P# 5::rvv{L$jsbff#$9?` r-