corSymm package:nlme R Documentation _G_e_n_e_r_a_l _C_o_r_r_e_l_a_t_i_o_n _S_t_r_u_c_t_u_r_e _D_e_s_c_r_i_p_t_i_o_n: This function is a constructor for the 'corSymm' class, representing a general correlation structure. The internal representation of this structure, in terms of unconstrained parameters, uses the spherical parametrization defined in Pinheiro and Bates (1996). Objects created using this constructor must later be initialized using the appropriate 'Initialize' method. _U_s_a_g_e: corSymm(value, form, fixed) _A_r_g_u_m_e_n_t_s: value: an optional vector with the parameter values. Default is 'numeric(0)', which results in a vector of zeros of appropriate dimension being assigned to the parameters when 'object' is initialized (corresponding to an identity correlation structure). form: a one sided formula of the form '~ t', or '~ t | g', specifying a time covariate 't' and, optionally, a grouping factor 'g'. A covariate for this correlation structure must be integer valued. When a grouping factor is present in 'form', the correlation structure is assumed to apply only to observations within the same grouping level; observations with different grouping levels are assumed to be uncorrelated. Defaults to '~ 1', which corresponds to using the order of the observations in the data as a covariate, and no groups. fixed: an optional logical value indicating whether the coefficients should be allowed to vary in the optimization, or kept fixed at their initial value. Defaults to 'FALSE', in which case the coefficients are allowed to vary. _V_a_l_u_e: an object of class 'corSymm' representing a general correlation structure. _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. (1996) "Unconstrained Parametrizations for Variance-Covariance Matrices", Statistics and Computing, 6, 289-296. Pinheiro, J.C., and Bates, D.M. (2000) "Mixed-Effects Models in S and S-PLUS", Springer. _S_e_e _A_l_s_o: 'Initialize.corSymm', 'summary.corSymm' _E_x_a_m_p_l_e_s: ## covariate is observation order and grouping factor is Subject cs1 <- corSymm(form = ~ 1 | Subject) # 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) # example gls(..., corSpher ...) # Pinheiro and Bates, pp. 261, 263 fm1Wheat2 <- gls(yield ~ variety - 1, Wheat2) # p. 262 fm2Wheat2 <- update(fm1Wheat2, corr = corSpher(c(28, 0.2), form = ~ latitude + longitude, nugget = TRUE)) # example gls(..., corSymm ... ) # Pinheiro and Bates, p. 251 fm1Orth.gls <- gls(distance ~ Sex * I(age - 11), Orthodont, correlation = corSymm(form = ~ 1 | Subject), weights = varIdent(form = ~ 1 | age))