lambda               package:mixtools               R Documentation

_L_o_c_a_l _E_s_t_i_m_a_t_i_o_n _f_o_r _L_a_m_b_d_a _i_n _M_i_x_t_u_r_e_s _o_f _R_e_g_r_e_s_s_i_o_n_s

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

     Return local estimates of the mixing proportions from each
     component of a mixture of regressions model using output from an
     EM algorithm.

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

     lambda(z, x, xi, h = NULL, kernel = c("Gaussian", "Beta", 
            "Triangle", "Cosinus", "Optcosinus"), g = 0)

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

       z: An nxk matrix of posterior probabilities obtained from the EM
          algorithm.

       x: A vector of values for which the local estimation is
          calculated.

      xi: An nx(p-1) matrix of the predictor values.

       h: The bandwidth controlling the size of the window used for the
          local estimation.

  kernel: The type of kernel to be used for the local estimation.

       g: A shape parameter required for the symmetric beta kernel. 
          The default is 'g' = 0 which yields the uniform kernel.  Some
          common values are 'g' = 1 for the Epanechnikov kernel, 'g' =
          2 for the biweight kernel, and 'g' = 3 for the triweight
          kernel.

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

     'lambda' returns local estimates of the mixing proportions for the
     inputted 'x' vector.

_N_o_t_e:

     'lambda' is for use within 'regmixEM.loc'.

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

     'regmixEM.loc'

