\name{H_environmental} \alias{environmental} \docType{data} \title{ Atmospheric environmental conditions in New York City } \description{ Daily measurements of ozone concentration, wind speed, temperature and solar radiation in New York City from May to September of 1973. } \usage{environmental} \format{ A data frame with 111 observations on the following 4 variables. \describe{ \item{ozone}{Average ozone concentration (of hourly measurements) of in parts per billion.} \item{radiation}{Solar radiation (from 08:00 to 12:00) in langleys.} \item{temperature}{Maximum daily emperature in degrees Fahrenheit.} \item{wind}{Average wind speed (at 07:00 and 10:00) in miles per hour.} } } \source{ 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 \emph{Symposium on Atmospheric Diffusion and Air Pollution}, pages 125--128. American Meterological Society, Boston. } \author{ Documentation contributed by Kevin Wright. } \references{ Cleveland, William S. (1993). \emph{Visualizing Data}. Hobart Press, Summit, New Jersey. } \examples{ # 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)") }) } \keyword{datasets}