summary.nlsList             package:nlme             R Documentation

_S_u_m_m_a_r_i_z_e _a_n _n_l_s_L_i_s_t _O_b_j_e_c_t

_D_e_s_c_r_i_p_t_i_o_n:

     The 'summary' function is applied to each 'nls' component of
     'object' to produce summary information on the individual fits,
     which is organized into a list of summary statistics. The returned
     object is suitable for printing with the 'print.summary.nlsList'
     method.

_U_s_a_g_e:

     ## S3 method for class 'nlsList':
     summary(object, ...)

_A_r_g_u_m_e_n_t_s:

  object: an object inheriting from class 'nlsList', representing a
          list of 'nls' fitted objects. 

     ...: optional arguments to the 'summary.lmList' method. One such
          optional argument is 'pool', a logical value indicating
          whether a pooled estimate of the residual standard error
          should be used. Default is 'attr(object, "pool")'. 

_V_a_l_u_e:

     a list with summary statistics obtained by applying 'summary' to
     the elements of 'object', inheriting from class 'summary.nlsList'.
     The components of 'value' are: 

    call: a list containing an image of the 'nlsList' call that
          produced 'object'. 

parameters: a three dimensional array with summary information on the
          'nls' coefficients. The first dimension corresponds to the
          names of the 'object' components, the second dimension is
          given by   '"Value"', '"Std. Error"', '"t value"', and
          '"Pr(>|t|)"', corresponding, respectively, to the coefficient
          estimates and their associated standard errors, t-values, and
          p-values. The third dimension is given by the coefficients
          names. 

correlation: a three dimensional array with the  correlations between
          the individual 'nls' coefficient estimates. The first
          dimension corresponds to the names of the 'object'
          components. The third dimension is given by the coefficients
          names. For each coefficient, the rows of the associated array
          give the correlations between that coefficient and the
          remaining coefficients, by 'nls' component. 

cov.unscaled: a three dimensional array with the unscaled
          variances/covariances for the individual 'lm' coefficient
          estimates (giving the estimated variance/covariance for the
          coefficients, when multiplied by the estimated residual
          errors). The first dimension corresponds to the names of the
          'object' components. The third dimension is given by the
          coefficients names. For each coefficient, the rows of the
          associated array give the unscaled covariances between that
          coefficient and the remaining coefficients, by 'nls'
          component. 

      df: an array with the number of degrees of freedom for the model
          and for residuals, for each 'nls' component. 

df.residual: the total number of degrees of freedom for residuals,
          corresponding to the sum of residuals df of all 'nls'
          components. 

    pool: the value of the 'pool' argument to the function. 

     RSE: the pooled estimate of the residual standard error.

   sigma: a vector with the residual standard error estimates for the
          individual 'lm' fits. 

_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:

     'nlsList', 'summary'

_E_x_a_m_p_l_e_s:

     data(Loblolly)
     fm1 <- nlsList(SSasymp, Loblolly)
     summary(fm1)

