Variogram.default            package:nlme            R Documentation

_C_a_l_c_u_l_a_t_e _S_e_m_i-_v_a_r_i_o_g_r_a_m

_D_e_s_c_r_i_p_t_i_o_n:

     This method function calculates the semi-variogram for an
     arbitrary vector 'object', according to the distances in
     'distance'. For each pair of elements x,y in 'object', the
     corresponding semi-variogram is (x-y)^2/2. The semi-variogram is
     useful for identifying and modeling spatial correlation structures
     in observations with constant expectation and constant variance.

_U_s_a_g_e:

     ## Default S3 method:
     Variogram(object, distance, ...)

_A_r_g_u_m_e_n_t_s:

  object: a numeric vector with the values to be used for calculating
          the semi-variogram, usually a residual vector from a fitted
          model.

distance: a numeric vector with the pairwise distances corresponding to
          the elements of 'object'. The order of the elements in
          'distance' must correspond to the pairs '(1,2), (1,3), ...,
          (n-1,n)', with 'n' representing the length of 'object', and
          must have length 'n(n-1)/2'.

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

_V_a_l_u_e:

     a data frame with columns 'variog' and 'dist' representing,
     respectively, the semi-variogram values and the corresponding
     distances. The returned value inherits from class 'Variogram'.

_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:

     Cressie, N.A.C. (1993), "Statistics for Spatial Data", J. Wiley &
     Sons.

_S_e_e _A_l_s_o:

     'Variogram.gls', 'Variogram.lme', 'plot.Variogram'

_E_x_a_m_p_l_e_s:

     ## Not run: 
     fm1 <- lm(follicles ~ sin(2 * pi * Time) + cos(2 * pi * Time), Ovary,
               subset = Mare == 1)
     Variogram(resid(fm1), dist(1:29))[1:10,]
     ## End(Not run)

