fitCitySeason {tsModel}R Documentation

Fit seasonally varying coefficient model

Description

Fit a seasonally varying coefficient model to NMMAPS data

Usage

fitCitySeason(data, pollutant = "l1pm10tmean", cause = "death",
              season = c("none", "periodic", "factor2"),
              tempModel = c("default", "rm7", "tempInt", "SeasonInt"),
              dfyr.Time = 7, pdfyr.time = 0.15, df.Temp = 6, df.Dew = 3,
              df.Season = 1, obsThreshold = 50, extractors = NULL)

Arguments

data data frame for an NMMAPS city
pollutant name of pollutant variable
cause name of cause of death; choices are "death" (all non-accidental), "cvd" (cardiovascular), or "resp" (respiratory)
season type of seasonal model to fit
tempModel type of temperature model to use
dfyr.Time number of degrees of freedom per calendar year of data to use in the smooth function of time
pdfyr.time fraction of the degrees of freedom used in the overall smooth function of time to use in the smooth function of time specific to the older age category
df.Temp degrees of freedom to use in the smooth function of temperature
df.Dew degrees of freedom to use in the smooth function of dew point temperature
df.Season number of sine/cosine pairs to include in the "periodic" model
obsThreshold minimum number of observations required before a model can be fit to the data
extractors a list of functions which extract elements of the "glm" object.

Details

This function fits a seasonally varying coefficient model to data from the NMMAPS study using two different seasonal models. The first is a step function model ("factor2") which uses indicators for the seasons. The second is a hamonic model ("periodic") which uses sines and cosines.

Value

An object of class "glm" is returned.

References

Peng RD, Dominici F, Pastor-Barriuso R, Zeger SL, Samet JM (2005). “Seasonal Analyses of Air Pollution and Mortality in 100 US Cities,” American Journal of Epidemiology, 161 (6), 585–595.


[Package tsModel version 0.5-1 Index]