intervals.gls              package:nlme              R Documentation

_C_o_n_f_i_d_e_n_c_e _I_n_t_e_r_v_a_l_s _o_n _g_l_s _P_a_r_a_m_e_t_e_r_s

_D_e_s_c_r_i_p_t_i_o_n:

     Approximate confidence intervals for the parameters in the linear
     model represented by 'object' are obtained, using a normal
     approximation to the distribution of the (restricted) maximum
     likelihood estimators (the estimators are assumed to have a normal
     distribution centered at the true parameter values and with
     covariance matrix equal to the negative inverse Hessian matrix of
     the (restricted) log-likelihood evaluated at the estimated
     parameters). Confidence intervals are obtained in an unconstrained
     scale first, using the normal approximation, and, if necessary,
     transformed to the constrained scale.

_U_s_a_g_e:

     ## S3 method for class 'gls':
     intervals(object, level, which, ...)

_A_r_g_u_m_e_n_t_s:

  object: an object inheriting from class 'gls', representing a
          generalized least squares fitted linear model.

   level: an optional numeric value for the interval confidence level.
          Defaults to 0.95.

   which: an optional character string specifying the subset of
          parameters for which to construct the confidence intervals.
          Possible values are '"all"' for all parameters, '"var-cov"'
          for the variance-covariance parameters only, and '"coef"' for
          the linear model coefficients  only. Defaults to '"all"'.

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

_V_a_l_u_e:

     a list with components given by data frames with rows
     corresponding to parameters and columns 'lower', 'est.', and
     'upper' representing respectively lower confidence limits, the
     estimated values, and upper confidence limits for the parameters.
     Possible components are: 

    coef: linear model coefficients, only present when 'which' is not
          equal to '"var-cov"'.

corStruct: correlation parameters, only present when 'which' is not
          equal to '"coef"' and a  correlation structure is used in
          'object'.

 varFunc: variance function parameters, only present when 'which' is
          not equal to '"coef"' and a variance function structure is
          used in 'object'.

   sigma: residual standard error.

_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:

     'gls', 'print.intervals.gls'

_E_x_a_m_p_l_e_s:

     data(Ovary)
     fm1 <- gls(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), Ovary,
                correlation = corAR1(form = ~ 1 | Mare))
     intervals(fm1)

