hunua                  package:VGAM                  R Documentation

_H_u_n_u_a _R_a_n_g_e_s _d_a_t_a

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

     The 'hunua' data frame has 392 rows and 18 columns. Altitude is
     explanatory, and there are binary responses  (presence/absence =
     1/0 respectively) for 17 plant species.

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

     data(hunua)

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

     This data frame contains the following columns:

     _a_g_a_a_u_s Agathis australis, or Kauri

     _b_e_i_t_a_w Beilschmiedia tawa, or Tawa

     _c_o_r_l_a_e Corynocarpus laevigatus

     _c_y_a_d_e_a Cyathea dealbata

     _c_y_a_m_e_d Cyathea medullaris

     _d_a_c_c_u_p Dacrydium cupressinum

     _d_a_c_d_a_c Dacrycarpus dacrydioides

     _e_l_a_d_e_n Elaecarpus dentatus

     _h_e_d_a_r_b Hedycarya arborea

     _h_o_h_p_o_p Species name unknown

     _k_n_i_e_x_c Knightia excelsa, or Rewarewa

     _k_u_n_e_r_i Kunzea ericoides

     _l_e_p_s_c_o Leptospermum scoparium

     _m_e_t_r_o_b Metrosideros robusta

     _n_e_s_l_a_n Nestegis lanceolata

     _r_h_o_s_a_p Rhopalostylis sapida

     _v_i_t_l_u_c Vitex lucens, or Puriri

     _a_l_t_i_t_u_d_e meters above sea level

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

     These were collected from the Hunua Ranges, a small forest in
     southern Auckland, New Zealand. At 392 sites in the forest, the
     presence/absence of 17 plant species was recorded, as well as the
     altitude.  Each site was of area size 200m^2.

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

     Dr Neil Mitchell, University of Auckland.

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

     'waitakere'.

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

     # Fit a GAM using vgam() and compare it with the Waitakere Ranges one
     data(hunua)
     fit.h = vgam(agaaus ~ s(altitude), binomialff, hunua)
     ## Not run: 
     plot(fit.h, se=TRUE, lcol="red", scol="red",
          main="Red is Hunua, Blue is Waitakere") 
     ## End(Not run)
     predict(fit.h, hunua, type="response")[1:3]

     data(waitakere)
     fit.w = vgam(agaaus ~ s(altitude), binomialff, waitakere)
     ## Not run: 
     plot(fit.w, se=TRUE, lcol="blue", scol="blue", add=TRUE) 
     ## End(Not run)
     predict(fit.w, hunua, type="response")[1:3]        # Same as above? 

