Seasonal Package and Autoplot Function

seasonal Package

Inbuilt seasonal functions

library(seasonal)
m <- seas(AirPassengers)
plot(m)

seasonalview create a shiny app using the which has a graph made via dygraphs package.

library(dygraphs)
dataplot<-cbind(trend=m[["data"]][,"trend"], AirPassengers)
p <- dygraph(dataplot)
p <- dygraphs::dyOptions(p, gridLineColor = "#E1E5EA", axisLineColor = "#303030", drawPoints
=TRUE, strokeWidth = 2, colors = c("blue","red"))%>% dyRangeSelector()
p

You can compare this to the

library(seasonalview)
view(m)

Autoplot Function From forecast

You can use the autoplot function to produce a ggplot object of their equivalent Acf, Pacf, Ccf, taperedacf and taperedpacf functions.

autoplot(object, ci = 0.95, ...)

kable(head(WWWusage))

plot(WWWusage)

          Arww<-Arima(WWWusage, order=c(3,1,0))
          Arww<-forecast(Arww,h=50) 
          plot(Arww)

autoplot(WWWusage, colour="red",  alpha = 0.5, xlab = "Time", ylab = "WWWusage")

          Arww<-Arima(WWWusage, order=c(3,1,0))
          Arww<-forecast(Arww,h=50) 
          autoplot(Arww, colour="red",  alpha = 0.5, xlab = "Time", ylab = "WWWusage")

For GLMs model checking with autoplot from ggfortify

ggfortify is Data Visualization Tools for Statistical Analysis Results https://cran.r-project.org/web/packages/ggfortify/ggfortify.pdf. The package offers a single plotting interface for these analysis results and plots in a unified style using ggplot2.

model<-glm(famit~famib, data=Data)

library(ggfortify)

Loading required package: ggplot2

autoplot(model, colour="red")