spTimer (version 0.8)

NYdata: Observations of ozone concentration levels, maximum temperature and wind speed.

Description

This data set contains values of daily 8-hour maximum average ozone concentrations (parts per billion (ppb)), maximum temperature (in degree Celsius), wind speed (knots), and relative humidity, obtained from 28 monitoring sites of New York, USA. Total 4 seperate subset datasets are created from NYdata that contains same variables as NYdata. 1. DataFit: This data is used for model fitting, contains 20 monitoring locations with 62 days observations; total 1200 rows. 2. DataValPred: This data is used for model validation for spatial prediction, contains 8 monitoring locations with 60 days observations; total 480 rows. 3. DataValFore: This data is used for model validation for temporal prediction in the unobserved locations, contains 8 monitoring locations with 2 days observations; total 8 rows. 4. DataFitFore: This data is used for model validation for temporal prediction in the observed locations, contains 20 monitoring locations with 2 days observations; total 40 rows. We also include a dataset that contains gridded observations over NY state. NYgrid: This dataset contains total 6200 rows for 62 days of observations for 10x10 = 100 grid points.

Usage

NYdata

format

Columns for NYdata: each contains 1798 observations.

• 1st col = Site index (s.index),
• 2nd col = Longitude,
• 3rd col = Latitude,
• 4th col = Year,
• 5th col = Month,
• 6th col = Day,
• 7th col = Ozone (o8hrmax),
• 8th col = Maximum temperature (cMAXTMP),
• 9th col = Wind speed (WDSP).
• 10th col = Relative humidity (RH).

source

US EPA

See Also

DataFit, DataFitFore, DataValFore, DataValPred, NYgrid.

Examples

##
  library("spTimer")
# NY data
  data(NYdata)
  head(NYdata)
# plots in NY map
  NYsite<-unique(cbind(NYdata[,1:3]))
  head(NYsite)
# map
  library(maps)
  map(database="state",regions="new york")
  points(NYsite[,2:3],pch=19)

# DataFit
  data(DataFit)
  head(DataFit)
# DataValPred
  data(DataValPred)
  head(DataValPred)
# DataValFore
  data(DataValFore)
  head(DataValFore)
# DataFitFore
  data(DataFitFore)
  head(DataFitFore)

# Plot fitted and validation locations in map
  fit.coords<-unique(cbind(DataFit[,1:3]))
  val.coords<-unique(cbind(DataValPred[,1:3]))

  library(maps)
  map(database="state",regions="new york")
  points(fit.coords[,2:3],pch=19,col=2)
  points(val.coords[,2:3],pch=7,col=1)
  legend(x=-78,y=41.5,pch=c(19,7),col=c(2,1),bty="n",
  legend=c("Fitted locations", "Validation locations"))

# Grid data
  data(NYgrid)
  head(NYgrid)
  grid.coords<-unique(cbind(NYgrid[,8:9]))
  library(maps)
  plot(grid.coords,pch=19,col=1)
  map(database="state",regions="new york",add=TRUE)

##