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)") })