pdMat-class              package:Matrix              R Documentation

_C_l_a_s_s _p_d_M_a_t, _p_o_s_i_t_i_v_e-_d_e_f_i_n_i_t_e _m_a_t_r_i_c_e_s

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

     A virtual class of parameterized positive-definite symmetric
     matrices.  This class describes the slots and methods that actual
     classes of positive-definite matrices are expected to incorporate.
      Some classes that inherit from 'pdMat' have additional slots and
     methods.

_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:

     Objects of class 'pdMat' are not constructed directly; only
     objects from classes that inherit from 'pdMat' are constructed.

_S_l_o_t_s:

     '_f_o_r_m': Object of class '"formula"', holds the formula for the
          object 

     '_N_a_m_e_s': Object of class '"character"' holding the names of the
          rows (and columns) of the positive-definite symmetric matrix
          represented by the object.

     '_p_a_r_a_m': '"numeric"' - the parameter vector.

     '_N_c_o_l': '"integer"' - the number of columns (and rows) in the
          matrix.

     '_f_a_c_t_o_r': '"matrix"' - a square-root factor of the matrix.

     '_l_o_g_D_e_t': '"numeric"' - the logarithm of the determinant of the
          factor.

_M_e_t_h_o_d_s:

     _c_o_e_r_c_e 'signature(from = "pdMat", to = "pdfactor")': extract a
          square-root factor of the matrix represented by the object. 
          This factor has a 'logDet' slot giving the logarithm of its
          determinant.  In the case of 'pdLogChol' these are both
          scalars and the 'logDet' attribute is the logarithm of the
          absolute value of the factor.

     _c_o_r_M_a_t_r_i_x 'signature(object = "pdMat")': Extract the correlation
          matrix corresponding to the positive-definite matrix
          represented by the object.  This method is present for back
          compatibility only.  The preferred way of extracting the
          correlation matrix is to coerce the object to the
          '"corrmatrix"' class.

     _d_i_m 'signature(x = "pdMat")': the dimensions of the
          positive-definite matrix represented by the object. 

     _f_o_r_m_u_l_a 'signature(x = "pdMat")': extract the formula 

     _i_s_I_n_i_t_i_a_l_i_z_e_d 'signature(object = "pdMat")': 'TRUE' if the object
          has been initialized, otherwise 'FALSE'.

     _l_o_g_D_e_t 'signature(object = "pdMat", covariate = "missing")': the
          logarithm of the determinant of the factor of the
          positive-definite matrix represented by the object. 

     _n_a_m_e_s 'signature(x = "pdMat")': extract a vector of names, which
          are both the column names and the row names of the
          positive-definite matrix represented by the object.

     _n_a_m_e_s<- 'signature(x = "pdMat")': assign the names,

     _p_d_F_a_c_t_o_r 'signature(object = "pdMat")': Extract the square root
          factor of positive-definite symmetric matrix represented by
          the object.  This method is present for back compatibility
          only.  The preferred way of extracting the factor is to
          coerce the object to the '"pdfactor"' class.

     _p_d_M_a_t_r_i_x 'signature(object = "pdMat")': Extract the
          positive-definite symmetric matrix represented by the object.
          This method is present for back compatibility only.  The
          preferred way of extracting the positive-definite symmetric
          matrix is to coerce the object to the '"pdmatrix"' class.

     _s_h_o_w 'signature(x = "pdMat")': show the object.

     _s_o_l_v_e 'signature(a = "pdMat", b = "missing")': Create an object of
          the same class representing the inverse of the
          positive-definite matrix.

     _s_u_m_m_a_r_y 'signature(object = "pdMat")':

_N_o_t_e:

     'pdMat' objects are primarily used to represent the
     variance-covariance matrix or the precision matrix of
     random-effects terms in mixed-effects models.  Frequently they are
     constructed from a formula only in the call to the mixed-effects
     modelling function then assigned a value as part of the
     initialization of the model.

_R_e_f_e_r_e_n_c_e_s:

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

     'pdCompSymm-class', 'pdDiag-class', 'pdLogChol-class',
     'pdIdent-class'

