boot                   package:eba                   R Documentation

_B_o_o_t_s_t_r_a_p _f_o_r _E_l_i_m_i_n_a_t_i_o_n-_b_y-_a_s_p_e_c_t_s _m_o_d_e_l_s

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

     Performs a bootstrap by resampling the individual data matrices.

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

       boot(D, R = 100, A = 1:I, s = rep(1/J, J))

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

       D: a 3d array consisting of the individual paired comparison
          matrices

       R: the number of bootstrap samples

       A: a list of vectors consisting of the stimulus aspects; the
          default is 1:I, where I is the number of stimuli

       s: the starting vector with default 1/J for all parameters,
          where J is the number of parameters

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

     The bootstrap function eba.boot is called automatically by boot.

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

       p: the matrix of bootstrap vectors

    stat: the matrix of bootstrap statistics, including parameter
          means, standard errors, and confidence limits

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

     Florian Wickelmaier wickelmaier@web.de

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

     'OptiPt'.

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

     data(pork)  # pork tasting data, 10 individual paired comparison matrices
     eba = OptiPt(apply(pork,1:2,sum))  # fit a BTL model
     b = boot(pork,200)  # resample 200 times

     plot(eba$estimate,b$stat[,'mean'],log='xy')
     abline(0,1,lty=3)

