waller               package:agricolae               R Documentation

_C_o_m_p_u_t_a_t_i_o_n_s _o_f _B_a_y_e_s_i_a_n _t-_v_a_l_u_e_s _f_o_r _m_u_l_t_i_p_l_e _c_o_m_p_a_r_i_s_o_n_s

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

     A Bayes rule for the symmetric multiple comparisons problem.

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

     waller(K, q, f, Fc)

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

       K: Is the loss ratio between type I and type II error 

       q: Numerator Degrees of freedom 

       f: Denominator Degrees of freedom 

      Fc: F ratio from an analysis of variance 

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

     K-RATIO (K): value specifies the Type 1/Type 2 error seriousness
     ratio for  the Waller-Duncan test. Reasonable values for KRATIO
     are 50, 100, and 500, which roughly correspond for the two-level
     case to ALPHA levels of 0.1, 0.05, and 0.01. By default, the
     procedure uses the default value of 100.

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

      K : Numeric integer > 1, examples 50, 100, 500

      q : Numeric

      f : Numeric

      Fc: Numeric

     ...

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

     Felipe de Mendiburu

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

     Waller, R. A. and Duncan, D. B. (1969). A Bayes Rule for the
     Symmetric Multiple Comparison Problem, Journal of the American
     Statistical Association 64, pages 1484-1504. 

     Waller, R. A. and Kemp, K. E. (1976) Computations of Bayesian
     t-Values for Multiple Comparisons, Journal of Statistical
     Computation and Simulation, 75, pages 169-172.

     Principles and procedures of statistics a biometrical approach
     Steel & Torry & Dickey. Third Edition 1997.

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

     'waller.test'

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

     # Table Duncan-Waller K=100, F=1.2 pag 649 Steel & Torry
     library(agricolae)
     K<-100
     Fc<-1.2
     q<-c(8,10,12,14,16,20,40,100)
     f<-c(seq(4,20,2),24,30,40,60,120)
     n<-length(q)
     m<-length(f)
     W.D <-rep(0,n*m)
     dim(W.D)<-c(n,m)
     for (i in 1:n) {
     for (j in 1:m) {
     W.D[i,j]<-waller(K, q[i], f[j], Fc)
     }}
     W.D<-round(W.D,2)
     dimnames(W.D)<-list(q,f)
     print(W.D)

