clusexpect                package:fpc                R Documentation

_E_x_p_e_c_t_e_d _v_a_l_u_e _o_f _t_h_e _n_u_m_b_e_r _o_f _t_i_m_e_s _a _f_i_x_e_d _p_o_i_n_t
_c_l_u_s_t_e_r _i_s _f_o_u_n_d

_D_e_s_c_r_i_p_t_i_o_n:

     A rough approximation of the expectation of the number of times a
     well separated fixed point cluster (FPC) of size 'n' is found in
     'ir' fixed point iterations of 'fixreg'.

_U_s_a_g_e:

     clusexpect(n, p, cn, ir)

_A_r_g_u_m_e_n_t_s:

       n: positive integer. Total number of points.

       p: positive integer. Number of independent variables.

      cn: positive integer smaller or equal to 'n'. Size of the FPC.

      ir: positive integer. Number of fixed point iterations.

_D_e_t_a_i_l_s:

     The approximation is based on the assumption that a well separated
     FPC is found iff all 'p+2' points of the initial coinfiguration
     come from the FPC. The value is 'ir' times the probability for
     this. For a discussion of this assumption cf. Hennig (2002).

_V_a_l_u_e:

     A number.

_A_u_t_h_o_r(_s):

     Christian Hennig chrish@stats.ucl.ac.uk <URL:
     http://www.homepages.ucl.ac.uk/~ucakche/>

_R_e_f_e_r_e_n_c_e_s:

     Hennig, C. (2002) Fixed point clusters for linear regression:
     computation and comparison, _Journal of Classification_ 19,
     249-276.

_S_e_e _A_l_s_o:

     'fixreg'

_E_x_a_m_p_l_e_s:

       clusexpect(500,4,150,2000)

