cor.acomp            package:compositions            R Documentation

_C_o_r_r_e_l_a_t_i_o_n_s _o_f _a_m_o_u_n_t_s _a_n_d _c_o_m_p_o_s_i_t_i_o_n_s

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

     Computes the correlation matrix in the various approaches of
     compositional and amount  data analysis.

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

               cor(x,y=NULL,...)
               ## Default S3 method:
               cor(x, y=NULL, use="all.obs", method=("pearson", 
         "kendall", "spearman"),...)
               ## S3 method for class 'acomp':
               cor(x,y=NULL,...)
               ## S3 method for class 'rcomp':
               cor(x,y=NULL,...)
               ## S3 method for class 'aplus':
               cor(x,y=NULL,...)
               ## S3 method for class 'rplus':
               cor(x,y=NULL,...)
               ## S3 method for class 'rmult':
               cor(x,y=NULL,...)
               

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

       x: a dataset, eventually of amounts or compositions

       y: a second dataset, eventually of amounts or compositions

     use: see 'cor'

  method: see 'cor'

     ...: further arguments to 'cor' e.g. 'use'

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

     The correlation matrix does not make much sense for compositions.

     In R versions older than v2.0.0, 'cor' was defined in package
     ``base'' instead of in ``stats''. This might produce some
     misfunction.

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

     The correlation  matrix.

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

     'var.acomp'

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

     data(SimulatedAmounts)
     mean.col(sa.lognormals)
     cor(acomp(sa.lognormals5[,1:3]),acomp(sa.lognormals5[,4:5]))
     cor(rcomp(sa.lognormals5[,1:3]),rcomp(sa.lognormals5[,4:5]))
     cor(aplus(sa.lognormals5[,1:3]),aplus(sa.lognormals5[,4:5]))
     cor(rplus(sa.lognormals5[,1:3]),rplus(sa.lognormals5[,4:5]))
     cor(acomp(sa.lognormals5[,1:3]),aplus(sa.lognormals5[,4:5]))

