transform-extract-methods        package:ghyp        R Documentation

_L_i_n_e_a_r _t_r_a_n_s_f_o_r_m_a_t_i_o_n _a_n_d _e_x_t_r_a_c_t_i_o_n _o_f _g_e_n_e_r_a_l_i_z_e_d _h_y_p_e_r_b_o_l_i_c _d_i_s_t_r_i_b_u_t_i_o_n_s

_D_e_s_c_r_i_p_t_i_o_n:

     This function may be useful when generalized hyperbolic
     distribution objects should be linearly transformed (`data` *
     multiplier + summand).  A generalized hyperbolic distribution
     object will be returned.

_U_s_a_g_e:

     ## S4 method for signature 'ghyp':
     transform(`_data`, summand, multiplier)

     ## S3 method for class 'ghyp':
     x[i = c(1, 2)]

_A_r_g_u_m_e_n_t_s:

   _data: An object inheriting from class 'ghyp'.

 summand: A 'vector'.

multiplier: A 'vector' or a 'matrix'.

       x: A multivariate generalized hyperbolic distribution inheriting
          from class 'ghyp'.

       i: Index specifying which dimensions to extract.

     ...: Arguments passed to 'transform'.

_V_a_l_u_e:

     An object of class 'ghyp'.

_A_u_t_h_o_r(_s):

     David Lthi

_S_e_e _A_l_s_o:

     'ghyp', 'fit.ghypuv' and 'fit.ghypmv'  for constructors of 'ghyp'
     objects.

_E_x_a_m_p_l_e_s:

       ## Mutivariate generalized hyperbolic distribution
       multivariate.ghyp <- ghyp(sigma=var(matrix(rnorm(9),ncol=3)), mu=1:3, gamma=-2:0)
       
       ## Dimension reduces to 2
       transform(multivariate.ghyp, multiplier=matrix(1:6,nrow=2), summand=10:11)
       
       ## Dimension reduces to 1
       transform(multivariate.ghyp, multiplier=1:3)
       
       ## Simple transformation
       transform(multivariate.ghyp, summand=100:102)
       
       ## Extract some dimension
       multivariate.ghyp[1]
       multivariate.ghyp[c(1, 3)]

