prepData: Function to prepare data frame for modelling
In davidcarslaw/deweather: Remove the influence of weather on air quality data

prepData

R Documentation

Function to prepare data frame for modelling

Description

This function takes a data frame that contains a field date and other variables and adds other common variables needed by the modelling functions. This function is run automatically by buildMod() but can be used separately for further analysis. These variables include:

Usage

prepData(
  mydata,
  add = c("hour", "hour.local", "weekday", "trend", "week", "jday", "month"),
  local.tz = "Europe/London",
  lag = NULL
)

Arguments

`mydata`	A data frame to process.
`add`	Names of explanatory variables to include.
`local.tz`	Used if hour needs to be expressed in local time. This can be useful for situations where the anthropogenic emissions source is strong and follows local time rather than UTC.
`lag`	Variables(s) to lag. Any variables included here will add new columns to the data frame. For example `lag = "ws"` with add a new columns `lag1ws`. Adding some variables here can improve the explanatory power of the models. Variables are lagged by one unit of time.

Details

hour The hour of the day from 0 to 23.
hour.local The hour in the local time zone. Note that the local time zone will need to be supplied (see local.tz). The purpose of using local time rather than UTC is that emissions can vary more strongly by local time rather than UTC.
weekday The day of the week.
trend The trend is calculated as a decimal year.
week The week of the year. Useful for taking account of long-term seasonal variations.
jday The Julian Day number.
month month of the year. Useful for taking account of long-term seasonal variations.