baran95                 package:ade4                 R Documentation

_A_f_r_i_c_a_n _E_s_t_u_a_r_y _F_i_s_h_e_s

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

     This data set is a list containing relations between sites and
     species linked to dates.

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

     data(baran95)

_F_o_r_m_a_t:

     This list contains the following objects:

     _f_a_u is a data frame 95 sites 33 species. 

     _p_l_a_n is a data frame 2 factors date and site. 

     _s_p_e_c_i_e_s._n_a_m_e_s is a vector of species latin names. 

_S_o_u_r_c_e:

     Baran, E. (1995) _Dynamique spatio-temporelle des peuplements de
     Poissons estuariens en Guine (Afrique de l'Ouest)_. Thse de
     Doctorat, Universit de Bretagne Occidentale.  Data collected by
     net fishing sampling in the Fatala river estuary.

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

     data(baran95)
     w <- dudi.pca(log(baran95$fau+1), scal = FALSE, scann = FALSE, 
         nf = 3)
     w1 <- within(w, baran95$plan$date, scann = FALSE)
     fatala <- ktab.within(w1)
     stat1 <- statis(fatala, scan = FALSE, nf = 3)
     w1 <- split(stat1$C.Co, baran95$plan$date)
     w2 <- split(baran95$plan$site, baran95$plan$date)
     par(mfrow = c(3,2))
     for (j in 1:6) {
         s.label(stat1$C.Co[,1:2], clab = 0,
         sub = tab.names(fatala)[j], csub = 3)
         s.class(w1[[j]][,1:2], w2[[j]], clab = 2, axese = FALSE,
         add.plot = TRUE)
     }
     par(mfrow = c(1,1))

     kplot(stat1, arrow = FALSE, traj = FALSE, clab = 2, uni = TRUE, 
         class = baran95$plan$site) #simpler

     mfa1 <- mfa(fatala, scan = FALSE, nf = 3)
     w1 <- split(mfa1$co, baran95$plan$date)
     w2 <- split(baran95$plan$site, baran95$plan$date)
     par(mfrow = c(3,2))
     for (j in 1:6) {
         s.label(mfa1$co[,1:2], clab = 0,
         sub = tab.names(fatala)[j], csub = 3)
         s.class(w1[[j]][,1:2], w2[[j]], clab = 2, axese=FALSE,
         add.plot = TRUE)
     }
     par(mfrow = c(1,1))

