lap.xts: LA Pollution-Mortality Study: Sampled Daily

In astsa: Applied Statistical Time Series Analysis

LA Pollution-Mortality Study: Sampled Daily

Description

Original data from a study of the effects of pollution and weather on mortality, LA, 1970-1979. These are 3652 daily observations for the 10 year period. The data set is an xts object indexed by Date.

Format

The format is: An xts object on 1970-01-01 / 1979-12-31 containing:
Data: double [3652, 11]
Columns: Tmort, Rmort, Cmort, Temp, Rhumid, CO, SO2, NO2, HC, Ozone, Part
Index: Date [3652] (TZ: "UTC")

Details

columns are time series	with names
(1) Total Mortality	Tmort
(2) Respiratory Mortality	Rmort
(3) Cardiovascular Mortality	Cmort
(4) Temperature	Temp
(5) Relative Humidity	Rhumid
(6) Carbon Monoxide	CO
(7) Sulfur Dioxide	SO2
(8) Nitrogen Dioxide	NO2
(9) Hydrocarbons	HC
(10) Ozone	Ozone
(11) Particulates	Part

Note

These are the original data from https://github.com/DSStoffer/dsstoffer.github.io/blob/main/files/LAP.pdf.

The weekly data in lap were taken from this data set last century. The details, however, were never entirely made clear and it's too late to get them now. It is easy to pull out the weekly averages from this data set, and how to do so is given in the Examples section below; the resulting data set will be slightly different than lap. The names for this data set are different from lap, the main difference is these names have capitals.

References

You can find demonstrations of astsa capabilities at FUN WITH ASTSA.

The most recent version of the package can be found at https://github.com/nickpoison/astsa/.

In addition, the News and ChangeLog files are at https://github.com/nickpoison/astsa/blob/master/NEWS.md.

The webpages for the texts and some help on using R for time series analysis can be found at https://nickpoison.github.io/.

See Also

lap

Examples

## Not run: 

library(xts)   # assumes package has been installed

plot(lap.xts$Cmort, col=4)   

lapw = apply.weekly(lap.xts, FUN=colMeans)  # get weekly averages

plot(lapw[,c('Cmort', 'Temp', 'Part')], col=astsa.col(2:4, .7), main=NA) 
addLegend(col=2:4, lty=1, lwd=2, ncol=3, bty="white")

sarima(lapw$Cmort, 0,1,1, no.constant=TRUE)  # fit ARIMA(0,1,1) to weekly Cmort

## End(Not run)

astsa documentation built on April 4, 2025, 12:40 a.m.