corFactor.corStruct           package:nlme           R Documentation

_F_a_c_t_o_r _o_f _a _c_o_r_S_t_r_u_c_t _O_b_j_e_c_t _M_a_t_r_i_x

_D_e_s_c_r_i_p_t_i_o_n:

     This method function extracts a transpose inverse square-root
     factor, or a series of transpose inverse square-root factors, of
     the correlation matrix, or list of correlation matrices, 
     represented by 'object'. Letting S denote a correlation matrix, a
     square-root factor of S is any square matrix L such that S = L'L.
     This method extracts L^(-t).

_U_s_a_g_e:

     ## S3 method for class 'corStruct':
     corFactor(object, ...)

_A_r_g_u_m_e_n_t_s:

  object: an object inheriting from class 'corStruct' representing a
          correlation structure, which must have been initialized
          (using 'Initialize').

     ...: some methods for this generic require additional arguments. 
          None are used in this method.

_V_a_l_u_e:

     If the correlation structure does not include a grouping factor,
     the returned value will be a vector with a transpose inverse
     square-root factor of the correlation matrix associated with
     'object' stacked column-wise.  If the correlation structure
     includes a grouping factor, the returned value will be a vector
     with transpose inverse square-root factors of the correlation
     matrices for each group, stacked by group and stacked column-wise
     within each group.

_N_o_t_e:

     This method function is used intensively in optimization
     algorithms and its value is returned as a vector for efficiency
     reasons. The 'corMatrix' method function can be used to obtain
     transpose inverse square-root factors in matrix form.

_A_u_t_h_o_r(_s):

     Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates
     bates@stat.wisc.edu

_S_e_e _A_l_s_o:

     'corFactor', 'corMatrix.corStruct', 'recalc.corStruct',
     'Initialize.corStruct'

_E_x_a_m_p_l_e_s:

     cs1 <- corAR1(form = ~1 | Subject)
     cs1 <- Initialize(cs1, data = Orthodont)
     corFactor(cs1)