corMatrix.corStruct           package:nlme           R Documentation

_M_a_t_r_i_x _o_f _a _c_o_r_S_t_r_u_c_t _O_b_j_e_c_t

_D_e_s_c_r_i_p_t_i_o_n:

     This method function extracts the correlation matrix (or its
     transpose inverse square-root factor), or list of correlation
     matrices (or their transpose inverse square-root factors)
     corresponding to 'covariate' and 'object'. Letting S denote a
     correlation matrix, a square-root factor of S is any square matrix
     L such that S=L'L. When 'corr = FALSE', this method extracts
     L^(-t).

_U_s_a_g_e:

     ## S3 method for class 'corStruct':
     corMatrix(object, covariate, corr, ...)

_A_r_g_u_m_e_n_t_s:

  object: an object inheriting from class 'corStruct' representing a
          correlation structure.

covariate: an optional covariate vector (matrix), or list of covariate
          vectors (matrices), at which values the correlation matrix,
          or list of correlation  matrices, are to be evaluated.
          Defaults to 'getCovariate(object)'.

    corr: a logical value. If 'TRUE' the function returns the
          correlation matrix, or list of correlation matrices,
          represented by 'object'. If 'FALSE' the function returns a
          transpose inverse square-root of the correlation matrix, or a
          list of transpose inverse square-root factors of the
          correlation matrices.

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

_V_a_l_u_e:

     If 'covariate' is a vector (matrix), the returned value will be an
     array with the corresponding correlation matrix (or its transpose
     inverse square-root factor). If the 'covariate' is a list of
     vectors (matrices), the returned value will be a list with the
     correlation matrices (or their transpose inverse square-root
     factors) corresponding to each component of 'covariate'.

_A_u_t_h_o_r(_s):

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

_R_e_f_e_r_e_n_c_e_s:

     Pinheiro, J.C., and Bates, D.M. (2000) "Mixed-Effects Models in S
     and S-PLUS", Springer.

_S_e_e _A_l_s_o:

     'corFactor.corStruct', 'Initialize.corStruct'

_E_x_a_m_p_l_e_s:

     cs1 <- corAR1(0.3)
     corMatrix(cs1, covariate = 1:4)
     corMatrix(cs1, covariate = 1:4, corr = FALSE)

     # Pinheiro and Bates, p. 225
     cs1CompSymm <- corCompSymm(value = 0.3, form = ~ 1 | Subject)
     cs1CompSymm <- Initialize(cs1CompSymm, data = Orthodont)
     corMatrix(cs1CompSymm)

     # Pinheiro and Bates, p. 226
     cs1Symm <- corSymm(value = c(0.2, 0.1, -0.1, 0, 0.2, 0),
                        form = ~ 1 | Subject)
     cs1Symm <- Initialize(cs1Symm, data = Orthodont)
     corMatrix(cs1Symm)

     # Pinheiro and Bates, p. 236 
     cs1AR1 <- corAR1(0.8, form = ~ 1 | Subject)
     cs1AR1 <- Initialize(cs1AR1, data = Orthodont)
     corMatrix(cs1AR1)

     # Pinheiro and Bates, p. 237 
     cs1ARMA <- corARMA(0.4, form = ~ 1 | Subject, q = 1)
     cs1ARMA <- Initialize(cs1ARMA, data = Orthodont)
     corMatrix(cs1ARMA)

     # Pinheiro and Bates, p. 238 
     spatDat <- data.frame(x = (0:4)/4, y = (0:4)/4)
     cs1Exp <- corExp(1, form = ~ x + y)
     cs1Exp <- Initialize(cs1Exp, spatDat)
     corMatrix(cs1Exp)