Ë
    £�Djš  ã            
       óö  — d Z ddlZddlmZmZmZ ddlmZ ddl	m
Z
 ddlmZ ddlmZ dd	lmZ dd
lmZ d„ Zd„ Zd„ Zd„ Zd„ Zd„ Zd,d„Zej6                  dfd„Zedk(  �r ej<                  g d¢g d¢g d¢g«      Z ej<                  g d¢g d¢g d¢g«      Z  ej<                  g d¢g d¢g d¢g«      Z!e!Z" ejF                  ej6                   ej6                   dg«      Z$ ejF                  g d¢«      Z$ ejF                  g d¢«      Z% ejF                  g d¢«      Z%d e$dd d!e%dd d"Z& ejN                  e&«      Z( e) e
e$e%ed#¬$«      «        e)ejT                  jW                  e%d   e&«      ejT                  jW                  e$d   e&«      z
  d!z  «       dZ, e) e
e,e$z  e(z  e,e%z  e(z  e"«      «       d%Z& e) ee$e%e"e&«      «        ejF                  d&d'gd'd&gg«      Z- e) ed"d(ge-d)d*«      «       d+Z. ed"d(ge-d)e.«      Z/ e) ej`                  e/d"d(gk  jc                  d«      d«      d&z  e.z  «        e) eej6                    ejd                  d)«      z   ejf                  d)«      e"dd)…dd)…f   d)«      «       yy)-a2  Multivariate Distribution

Probability of a multivariate t distribution

Now also mvstnormcdf has tests against R mvtnorm

Still need non-central t, extra options, and convenience function for
location, scale version.

Author: Josef Perktold
License: BSD (3-clause)

Reference:
Genz and Bretz for formula

é    N)Ú	integrateÚstatsÚspecial)Úchié   )Úmvstdnormcdf)Úexp)Úlog)Úgamma)Úgammalnc                 ó˜   — ||dz  dz
  z  t        j                  | dz  «      z  }|t        j                  |dz  «      d|dz  z  z  z  }|S )zpdf of chi-square distributionç       @r   é   )Únpr	   r   r   )ÚselfÚxÚdfÚPxs       úrC:\Crop_Prediction\Backend\crop-ai-system\venv\Lib\site-packages\statsmodels/sandbox/distributions/multivariate.pyÚchi2_pdfr      sQ   € ð 
ˆR�‰V�A‰X‰”r—v‘v˜q˜b ™f“~Ñ	%€BØŒ'�-‰-˜˜3™Ó
  R¨¡V¡Ñ
,Ñ,€BØ€Ió    c                 ó–   — |dz
  t        | «      z  |  | z  dz  z   |dz  dz
  t        d«      z  z
  t        |dz  «      z
  }t        |«      S ©Nç      ð?ç      à?r   r   )Únp_logÚsps_gammalnÚnp_exp©r   r   Útmps      r   Úchi_pdfr!   #   sT   € Øˆb‰5”&˜“)Ñ
 ˜r !™t C™xÑ
(¨B¨s©F°1©H´f¸S³kÑ+AÑ
AÜ˜˜3™Óñ €Cä�#‹;Ðr   c                 ó„   — |dz
  t        | «      z  |  | z  dz  z   |dz  dz
  t        d«      z  z
  t        |dz  «      z
  }|S r   )r   r   r   s      r   Ú
chi_logpdfr#   )   sO   € Øˆb‰5”&˜“)Ñ
 ˜r !™t C™xÑ
(¨B¨s©F°1©H´f¸S³kÑ+AÑ
AÜ˜˜3™Óñ €Cà€Jr   c           
      ó´   — t        j                  |dz   «      }t        | |«      }|t        t	        | |z  |z  | |z  |z  |dd¬«      «      z  }t        |«      }|S )Nr   é@B ç�íµ ÷Æ°>©ÚmaxptsÚabseps)r   Úsqrtr#   r   r   r   )ÚsÚaÚbÚRr   Úsqrt_dfÚrets          r   Úfunbghr1   .   sc   € Ü�g‰g�b˜‘f‹o€GÜ
�Q�rÓ
€CØŒ6”,˜q ™s 7™{¨A¨a©C°©K¸Ø07ÀôFó Gñ G€Cä
�‹+€CØ€Jr   c           
      óð   — t        |«      }t        j                  |«      }t        |dz
  t	        | «      z  | | z  dz  z
  «      t        | |z  |z  | |z  |z  |t        j                  |d«         dd¬«      z  S )Nr   r   éÿÿÿÿr%   ç-Cëâ6?r'   )Úlenr   r*   r   r   r   Útril_indices)r+   r,   r-   r.   r   Únr/   s          r   Úfunbgh2r8   6   sw   € ÜˆA‹€AÜ�g‰g�b‹k€Gä�2�a‘4œ ›Ñ" 1 Q¡3 s¡7Ñ*Ó+Ü˜!˜A™#˜g™+ q¨¡s¨7¡{°A´b·o±oÀaÈÓ6LÑ4MØ!(°ô7ñ7ð 7r   c                 óX   — t        j                  dd| dz  z
  «      t        | dz  «      z  S )Nr   r   r   )r   ÚpowerÚ	sps_gamma)r   s    r   Ú	bghfactorr<   >   s)   € Ü�8‰8�C˜˜2˜c™6™Ó"¤Y¨r°#©vÓ%6Ñ6Ð6r   c                 óè   — t        | |||fddd¬«      }|�|j                  |«       t        j                  |d|z
  g|«      \  }}	t	        j
                  t        ||	fi |¤Ž\  }
}|
t        |«      z  }|S )a8  
    Probability of rectangular area of standard t distribution

    assumes mean is zero and R is correlation matrix

    Notes
    -----
    This function does not calculate the estimate of the combined error
    between the underlying multivariate normal probability calculations
    and the integration.
    r4   g{®Gáz„?é–   )ÚargsÚepsabsÚepsrelÚlimitr   )ÚdictÚupdater   Úppfr   Úquadr8   r<   )r,   r-   r.   r   ÚiepsÚquadkwdsÚmvstkwdsÚkwdsÚlowerÚupperÚresÚerrÚprobs                r   Ú
mvstdtprobrP   B   sy   € ô �a˜˜A˜r�]¨4¸ÀCÔH€DØÐØ�‰�HÔÜ—7‘7˜D ! d¡(Ð+¨RÓ0�L€Eˆ5Ü�~‰~œg u¨eÑ<°tÑ<�H€CˆØ”˜2“Ñ€DØ€Kr   c                 óˆ  — t        j                  | «      } t        | «      }|t         j                  k(  rt        j                  |«      }n#t         j
                  j                  ||«      |z  }t         j
                  j                  t        j                  |«      ||f«      }| |t        j                  |«      dd…df   z  z   S )a  generate random variables of multivariate t distribution

    Parameters
    ----------
    m : array_like
        mean of random variable, length determines dimension of random variable
    S : array_like
        square array of covariance  matrix
    df : int or float
        degrees of freedom
    n : int
        number of observations, return random array will be (n, len(m))

    Returns
    -------
    rvs : ndarray, (n, len(m))
        each row is an independent draw of a multivariate t distributed
        random variable


    N)
r   Úasarrayr5   ÚinfÚonesÚrandomÚ	chisquareÚmultivariate_normalÚzerosr*   )ÚmÚSr   r7   Údr   Úzs          r   Úmultivariate_t_rvsr]   X   s�   € ô, 	�
‰
�1‹€AÜˆA‹€AØ	ŒR�V‰V‚|Ü�G‰G�A‹J‰ä�I‰I×Ñ  AÓ& rÑ)ˆÜ
�	‰	×%Ñ%¤b§h¡h¨q£k°!°Q°DÓ9€AØˆq”—‘˜“šA˜d˜FÑ#Ñ#Ñ#Ð#r   Ú__main__)r   r   r   )r   r   r   )r   r   r   )r   r   r   )r   r   r   )r   r   r   )r   r   r   )r   r   r   g      YÀ)ç¸…ëQ¸î¿r_   r_   )ç        r`   r`   )ç¸…ëQ¸î?ra   ra   r3   é   g      $@r&   )r)   é   r   r   g      4@r   é   i'  )gñhãˆµøä>NN)4Ú__doc__Únumpyr   Úscipyr   r   r   Úscipy.statsr   Úextrasr   r	   r   r
   r   Úscipy.specialr   r;   r   r   r   r!   r#   r1   r8   r<   rP   rS   r]   Ú__name__rR   ÚcorrÚ
corr_indepÚ
corr_equalr.   Úarrayr,   r-   r   r*   r/   ÚprintÚtÚcdfr+   rZ   ÚnobsÚrvstÚsumÚallrT   rX   © r   r   ú<module>rx      s„  ðñó  ß +Ñ +Ý å  å Ý Ý ,Ý 0òòòò
ò7ò7óð, !#§¡¨!ó $ðD ˆzÓØˆ2�:‰:’}¢WªYÐ7Ó8€DØ�—‘š[ª²Ð9Ó:€JØ�—‘š_ª[ºÐEÓF€JØ€AØˆ�‰�2—6‘6�'˜2Ÿ6™6˜' &Ð)Ó*€AØˆ�‰Ò$Ó%€AØˆ�‰’Ó€AØˆ�‰Ò"Ó#€AØ€A�a€DØ€A�a€DØ	€BØˆb�g‰g�b‹k€GÙ	‰,�q˜!˜T¨$Ô
/Ô0ñ 
ˆ5�7‰7�;‰;�q˜‘t˜RÓ  5§7¡7§;¡;¨q°©t°RÓ#8Ñ8¸1Ñ
<Ô=à	€AÙ	‰,�q˜‘s˜7‘{ A a¡C¨¡K°Ó
3Ô4ð 	€BÙ	‰*�Q˜˜1˜bÓ
!Ô"àˆ�‰�2�b�'˜2˜b˜'Ð"Ó#€AÙ	Ñ
˜c #˜Y¨¨1¨aÓ
0Ô1à€DÙ˜s 3˜i¨¨A¨tÓ4€DÙ	ˆ&ˆ"�&‰&�$˜˜C�y‘.×%Ñ% aÓ(¨Ó
+¨bÑ
0°4Ñ
7Ô8Ù	‰*�b—f‘f�W˜W˜RŸW™W Q›ZÑ'¨¨¯©°!«°a¸¸¸¸2¸A¸2¸±hÀÓ
BÔCððE r   