acceptanceProbability        package:designGG        R Documentation

_C_o_m_p_u_t_e _t_h_e _a_c_c_e_p_t_a_n_c_e _p_r_o_b_a_b_i_l_i_t_y _f_o_r _e_a_c_h _u_p_d_a_t_e_d _d_e_s_i_g_n

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

     Compute the acceptance probability for each updated design. It
     depends on the current temperature value of simulated annealing
     process. This is a subfunction needed for 'designGG', but is not
     directly used.

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

         acceptanceProbability( designScore, newDesignScore, method, 
                                temperature )

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

designScore: score of current design. 

newDesignScore: score of updated design.  

  method: either "SA" (simulated annealing) or "MH".  (Metropolis
          Hastings)  

temperature: current temperature in simulated annealing process.  

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

     Yang Li <yang.li@rug.nl>, Gonzalo Vera
     <gonzalo.vera.rodriguez@gmail.com> 
      Rainer Breitling <r.breitling@rug.nl>, Ritsert Jansen
     <r.c.jansen@rug.nl>

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

     E. Wit and J. McClure. Statistics for Microarrays: Design,
     Analysis and Inference. (2004) Chichester: Wiley.  
      Y. Li, R. Breitling and R.C. Jansen. Generalizing genetical 
     genomics: the added value from environmental perturbation, Trends
     Genet (2008) 24:518-524. 
          Y. Li, M. Swertz, G. Vera, J. Fu, R. Breitling, and R.C.
     Jansen. designGG:  An R-package and Web tool for the optimal
     design of genetical genomics  experiments. (submitted) 
      http://gbic.biol.rug.nl/designGG

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

     'designGG'

