
    M/Ph              
          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j        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j#        ej         ej         dg          Z$ ej#        g d          Z$ ej#        g d          Z% ej#        g d           Z%d!e$dd<   d"e%dd<   d#Z& ej'        e&          Z( e) e
e$e%ed$%                      e)ej*        +                    e%d         e&          ej*        +                    e$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j#        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j0        e/d#d)gk     1                    d          d          d'z  e.z              e) eej          ej2        d*          z   ej3        d*          e"dd*dd*f         d*                     dS dS ).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

    N)	integratestatsspecial)chi   )mvstdnormcdf)exp)log)gamma)gammalnc                     ||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 distribution       @r      )npr	   r   r   )selfxdfPxs       n/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/statsmodels/sandbox/distributions/multivariate.pychi2_pdfr      sR     
RVAXrvqbf~~	%B'-3

RV
,,BI    c                     |dz
  t          |           z  |  | z  dz  z   |dz  dz
  t          d          z  z
  t          |dz            z
  }t          |          S N      ?      ?r   r   )np_logsps_gammalnnp_expr   r   tmps      r   chi_pdfr!   #   s]    b5&))
r!tCx
(BsF1HfSkk+A
A3 C#;;r   c                     |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   
chi_logpdfr#   )   sV    b5&))
r!tCx
(BsF1HfSkk+A
A3 CJr   c           
          t          j        |dz             }t          | |          }|t          t	          | |z  |z  | |z  |z  |dd                    z  }t          |          }|S )Nr   @B ư>maxptsabseps)r   sqrtr#   r   r   r   )sabRr   sqrt_dfrets          r   funbghr1   .   sz    gbfooG
Qr

C6,qs7{AaCK07F F F G G GC
++CJr   c           
         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   r%   -C6?r'   )lenr   r*   r   r   r   tril_indices)r+   r,   r-   r.   r   nr/   s          r   funbgh2r8   6   s    AAgbkkG2a4"1Q3s7*++!A#g+qs7{Aboa6L6L4M!(7 7 77 7r   c                 ^    t          j        dd| dz  z
            t          | dz            z  S )Nr   r   r   )r   power	sps_gamma)r   s    r   	bghfactorr<   >   s-    8C2c6""Yr#v%6%666r   h㈵>c                     t          | |||fddd          }||                    |           t          j        |d|z
  g|          \  }}	t	          j        t          ||	fi |\  }
}|
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{Gz?   )argsepsabsepsrellimitNr   )dictupdater   ppfr   quadr8   r<   )r,   r-   r.   r   iepsquadkwdsmvstkwdskwdslowerupperreserrprobs                r   
mvstdtprobrQ   B   s     aAr]4CHHHDH7D!d(+R00LE5~gue<<t<<HC2DKr   c                    t          j        |           } t          |           }|t           j        k    rt          j        |          }n#t           j                            ||          |z  }t           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   asarrayr5   infonesrandom	chisquaremultivariate_normalzerosr*   )mSr   r7   dr   zs          r   multivariate_t_rvsr^   X   s    , 	
1AAA	RV||GAJJIA&&r)
	%%bhqkk!QD99AqAAAdF####r   __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      Y)Qr`   r`   )        ra   ra   )Q?rb   rb   r3      g      $@r&   )r)      r   r   g      4@r      i'  )r=   NN)4__doc__numpyr   scipyr   r   r   scipy.statsr   extrasr   r	   r   r
   r   scipy.specialr   r;   r   r   r   r!   r#   r1   r8   r<   rQ   rT   r^   __name__rS   corr
corr_indep
corr_equalr.   arrayr,   r-   r   r*   r/   printtcdfr+   r[   nobsrvstsumallrU   rY    r   r   <module>ry      s         + + + + + + + + + +                               , , , , , , 0 0 0 0 0 0      
  7 7 77 7 7   , !#! $ $ $ $D z2:}}}WWWYYY788D[[[9::J___[[[EFFJA26'26'&)**A$$$%%AA"""##AAaaaDAaaaD	BbgbkkG	E,,q!T$
/
/
/000 
E57;;qtR  57;;qtR#8#881
<===	A	E,,qs7{AaCK
3
3444 	B	E**Q1b
!
!"""2b'2b'"##A	E

c#Y1a
0
0111Ds3iAt44D	E&"&$Cy.%%a((
+
+b
04
7888	E**bfWWRWQZZ'!a2A2h
B
BCCC E r   