USprecip                package:spam                R Documentation

_M_o_n_t_h_l_y _t_o_t_a_l _p_r_e_c_i_p_i_t_a_t_i_o_n (_m_m) _f_o_r _A_p_r_i_l _1_9_4_8 _i_n _t_h_e _c_o_n_t_i_g_u_o_u_s _U_n_i_t_e_d _S_t_a_t_e_s

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

     This is a useful spatial data set of moderate to large size
     consisting of 11918  locations. See <URL:
     www.image.ucar.edu/GSP/Data/US.monthly.met/> for the source of
     these data.

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

     This data set is an array containing the following columns: 


     _l_o_n,_l_a_t Longitude-latitude position of monitoring stations

     _r_a_w Monthly total precipitation in millimeters for April 1948

     _a_n_o_m_a_l_y Preipitation anomaly for April 1948. 

     _i_n_f_i_l_l Indicator, which station values were observed (5906 out of
          the 11918) compared to which were estimated.


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

     <URL: www.image.ucar.edu/GSP/Data/US.monthly.met/>

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

     Johns, C., Nychka, D., Kittel, T., and Daly, C. (2003) Infilling
     sparse records of spatial fields. _Journal of the American
     Statistical Association_, 98, 796-806.

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

     'RMprecip'

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

     # plot
     ## Not run: 
     library(fields)

     data(USprecip)
     par(mfcol=c(2,1))
     quilt.plot(USprecip[,1:2],USprecip[,3])
     US( add=TRUE, col=2, lty=2)
     quilt.plot(USprecip[,1:2],USprecip[,4])
     US( add=TRUE, col=2, lty=2)
     ## End(Not run)

