agriculture             package:cluster             R Documentation

_E_u_r_o_p_e_a_n _U_n_i_o_n _A_g_r_i_c_u_l_t_u_r_a_l _W_o_r_k_f_o_r_c_e_s

_D_e_s_c_r_i_p_t_i_o_n:

     Gross National Product (GNP) per capita and percentage of the
     population working in agriculture for each country belonging to
     the European Union in 1993.

_U_s_a_g_e:

     data(agriculture)

_F_o_r_m_a_t:

     A data frame with 12 observations on 2 variables:

       [ , 1]  'x'  numeric  per capita GNP
       [ , 2]  'y'  numeric  percentage in agriculture

     The row names of the data frame indicate the countries.

_D_e_t_a_i_l_s:

     The data seem to show two clusters, the "more agricultural" one
     consisting of Greece, Portugal, Spain, and Ireland.

_S_o_u_r_c_e:

     Eurostat (European Statistical Agency, 1994): _Cijfers en feiten:
     Een statistisch portret van de Europese Unie_.

_R_e_f_e_r_e_n_c_e_s:

     Anja Struyf, Mia Hubert & Peter J. Rousseeuw (1996): Clustering in
     an Object-Oriented Environment. _Journal of Statistical Software_,
     *1*. <URL: http://www.stat.ucla.edu/journals/jss/>

_S_e_e _A_l_s_o:

     'agnes', 'daisy', 'diana'.

_E_x_a_m_p_l_e_s:

     data(agriculture)

     ## Compute the dissimilarities using Euclidean metric and without
     ## standardization
     daisy(agriculture, metric = "euclidean", stand = FALSE)

     ## 2nd plot is similar to Figure 3 in Struyf et al (1996)
     plot(pam(agriculture, 2))

     ## Plot similar to Figure 7 in Struyf et al (1996)
     ## Not run: plot(agnes(agriculture), ask = TRUE)


     ## Plot similar to Figure 8 in Struyf et al (1996)
     ## Not run: plot(diana(agriculture), ask = TRUE)

