ggdecompose: Visualisation of decomposed time series

In brisneve/ggplottimeseries: Visualisation of Decomposed Time Series with ggplot2

Description

These functions plots the observed, trend, seasonal, and random components of time series into one figure (ggdecompose) or into separate figures (ggobserve, ggtrend, ggseason, ggrandom, respectively). These functions also plots detrended and deseasonalised time series (ggdetrend and ggdeseason, respectively). These can be integrated with ggplot functions.

Usage

ggdecompose(x)
ggobserve(x)
ggtrend(x)
ggseason(x)
ggrandom(x)
ggdetrend(x)
ggdeseason(x)

Arguments

x	a data frame generated by either dts or dts2 functions.

Value

This returns to a plot.

Author(s)

Brisneve Edullantes

Examples

data(co2)
x <- dts2(co2, type ="additive")
#plots decomposed time series into one figure
ggdecompose(x)+
 xlab("Date")+
 ylab("Atmospheric Concentration of CO2")
#plots components of time series into separate figure
ggobserve(x)+
 xlab("Date")+
 ylab("Observed Atmospheric Concentration of CO2")

ggtrend(x)+
 xlab("Date")+
 ylab("Trend of Atmospheric Concentration of CO2")

ggseason(x)+
 xlab("Date")+
 ylab("Seasonality of Atmospheric Concentration of CO2")

ggrandom(x)+
 xlab("Date")+
 ylab("Random Variation of Atmospheric Concentration of CO2")

#plots detrended and deseasonalised Time Series

ggdetrend(x)

ggdeseason(x)

brisneve/ggplottimeseries documentation built on May 7, 2019, 3:08 p.m.