environmental            package:lattice            R Documentation

_A_t_m_o_s_p_h_e_r_i_c _e_n_v_i_r_o_n_m_e_n_t_a_l _c_o_n_d_i_t_i_o_n_s _i_n _N_e_w _Y_o_r_k _C_i_t_y

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

     Daily measurements of ozone concentration, wind speed, temperature
     and solar radiation in New York City from May to September of
     1973.

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

     environmental

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

     A data frame with 111 observations on the following 4 variables.

     _o_z_o_n_e Average ozone concentration (of hourly measurements) of in
          parts per billion.

     _r_a_d_i_a_t_i_o_n Solar radiation (from 08:00 to 12:00) in langleys.

     _t_e_m_p_e_r_a_t_u_r_e Maximum daily emperature in degrees Fahrenheit.

     _w_i_n_d Average wind speed (at 07:00 and 10:00) in miles per hour.

_A_u_t_h_o_r(_s):

     Documentation contributed by Kevin Wright.

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

     Bruntz, S. M., W. S. Cleveland, B. Kleiner, and J. L. Warner. 
     (1974). The Dependence of Ambient Ozone on Solar Radiation, Wind,
     Temperature, and Mixing Height.  In _Symposium on Atmospheric
     Diffusion and Air Pollution_, pages 125-128.  American
     Meterological Society, Boston.

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

     Cleveland, William S. (1993). _Visualizing Data_.  Hobart Press,
     Summit, New Jersey.

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

     # Scatter plot matrix with loess lines
     splom(~environmental,
       panel=function(x,y){
         panel.xyplot(x,y)
         panel.loess(x,y)
       }
     )

     # Conditioned plot similar to figure 5.3 from Cleveland
     attach(environmental)
     Temperature <- equal.count(temperature, 4, 1/2)
     Wind <- equal.count(wind, 4, 1/2)
     xyplot((ozone^(1/3)) ~ radiation | Temperature * Wind,
       aspect=1,
             prepanel = function(x, y) 
                     prepanel.loess(x, y, span = 1),
             panel = function(x, y){
                     panel.grid(h = 2, v = 2)
                     panel.xyplot(x, y, cex = .5)
                     panel.loess(x, y, span = 1)
             },
             xlab = "Solar radiation (langleys)",
             ylab = "Ozone (cube root ppb)")
     detach()

     # Similar display using the coplot function
     with(environmental,{
       coplot((ozone^.33) ~ radiation | temperature * wind,
       number=c(4,4),
       panel = function(x, y, ...) panel.smooth(x, y, span = .8, ...),
       xlab="Solar radiation (langleys)",
       ylab="Ozone (cube root ppb)")
     })

