venice                 package:VGAM                 R Documentation

_V_e_n_i_c_e _M_a_x_i_m_u_m _S_e_a _L_e_v_e_l_s

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

     The maximum heights of sea levels recorded at Venice, Italy,
     between 1931 and 1981.

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

     data(venice)

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

     A data frame with 51 observations on the following 11 variables.

     _y_e_a_r a numeric vector. 

     _r_1 a numeric vector; the highest recorded value. 

     _r_2,_r_3,_r_4,_r_5,_r_6,_r_7,_r_8,_r_9,_r_1_0 numeric vectors; the second highest
          recorded value down to the tenth highest recorded value. 

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

     The units are cm. In 1935 only the top six values were recorded.

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

     Pirazzoli, P. (1982) Maree estreme a Venezia (periodo 1872-1981).
     _Acqua Aria_, *10*, 1023-1039.

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

     Smith, R. L. (1986) Extreme value theory based on the _r_ largest
     annual events. _Journal of Hydrology_, *86*, 27-43.

     Rosen, O. and Cohen, A. (1996) Extreme Percentile Regression. In:
     Haerdle, W. and Schimek, M. G. (eds.) _Statistical Theory and
     Computational Aspects of Smoothing: Proceedings of the COMPSTAT
     '94 Satellite Meeting held in Semmering, Austria, 27-28 August
     1994_, Physica-Verlag: Heidelberg, pp.200-214.

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

     data(venice)
     ## Not run: 
     matplot(venice[["year"]], venice[,-1], xlab="Year", ylab="Sea level (cm)")
     ## End(Not run)

     y = as.matrix(venice[,paste("r",1:10,sep="")])
     fit1 = vgam(y ~ s(year, df=3), gumbel(R=365, mpv=TRUE),
                 data=venice, trace=TRUE, na.action=na.pass)
     fitted(fit1)[1:4,]

     ## Not run: 
     par(mfrow=c(2,1), xpd=TRUE)
     plot(fit1, se=TRUE, lcol="blue", llwd=2, slty="dashed")

     par(mfrow=c(1,1), bty="l", xpd=TRUE, las=1)
     qtplot(fit1, mpv=TRUE, lcol=c(1,2,5), tcol=c(1,2,5), 
            llwd=2, pcol="blue", tadj=0.1)
     ## End(Not run)

