fwdtrProfilePlot           package:Rfwdmv           R Documentation

_P_l_o_t _m_e_t_h_o_d _f_o_r _p_r_o_f_i_l_e._f_w_d_t_r _o_b_j_e_c_t_s

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

     Produces a plot of profile loglikelihoods of transformation
     parameters in a particular step of the forward search

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

     fwdtrProfilePlot(x, psfrag.labels = FALSE)

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

       x: a 'profile.fwdtr' object. 

psfrag.labels: a logical value.  If 'TRUE' then the x, y, and main
          labels are set to "xlab", "ylab", and "main" for replacement
          via the psfrag utility.

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

     This plot shows which variables show a sharp definition of the
     estimates of the transformation parameters and which are the
     variables whose value of lambda is not very well determined.

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

     an empty list is invisibly returned.

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

     Fabrizio Laurini

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

     Atkinson, A. C., Riani, M. and Cerioli, A. (2004)  Exploring
     Multivariate Data with the Forward Search.  Springer-Verlag New
     York.

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

     'fwdtr.object'

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

     data(mussels.dat)

     ## Forward search on untransformed data 
     ## Compute max lik. estimates of tramsformation parameters

     l.mle <- fwdtr(mussels.dat)

     ## Compute profile loglikelihoods for transformation parameters in the
     ## last step of the search and create an object of class profile.fwdtr

     l.profile.mle <- profile.fwdtr(l.mle)

     ## plot the profile loglikelihoods of transformation parameters for
     ## each variable 

     fwdtrProfilePlot(l.profile.mle)

     ## Test variables 2 and 5
     ## The forward is based on untransformed data for variables 1, 3 and 4
     ## sqrt for variable 2 and third root for variable 5

     l.mle <- fwdtr(mussels.dat, lambda = c(0.5, 1/3), col.to.transform = c(2, 5))

     ## build profile likelihood for transformed variables.
     ## Profile function takes into account that we have also untransformed variables.

     l.profile.mle <- profile.fwdtr(l.mle)
     fwdtrProfilePlot(l.profile.mle)

