ADDline: ‘ADDline’

In TSplotly: Create Interactive Plots on Time Series Dataset

Description

create a list of line data based on ARIMA(X) predicted result or ts function result(i.e. time series data)

Usage

ADDline(ARIMAmodel = NULL, XREG = NULL, TS = NULL, linetype = "TS",
  Name = NULL)

Arguments

ARIMAmodel	ARIMA model created by function auto.arima()
XREG	if using ARIMAX model, put in the regularized X matrix
TS	data created by ts() function
linetype	"TS" for time series data, "ARIMA" for ARIMA(X) predicted data
Name	title for this line

Details

This function ADDline is used to conduct a data transformation. It can take in original time-series data generated by function ts or fitted ARIMA(X) model generated by function auto.arima then take out four elements from those result to create a list which contains content that can be put in function add_lines or add_trace. So that we could add new lines in our plotly plot more easily.

Value

a list contains 4 elements:

X	data put in parameter "x" of plot_ly function
TEXT	rename the lable of variable X
Y	data put in parameter "y" of plot_ly function
NAME	title of the new line

Author(s)

SOCR team <http://socr.umich.edu/people/>

Examples

require(forecast)
require(zoo)
require(plotly)

#Firstly create a base plotly plot
Tempplot<-TSplot(48,modArima_train,as.matrix(X_test),title_size = 8,
ts_original = "Original time series",ts_forecast = "Predicted time series")

# Generate a new line with ADDline function
newline<-ADDline(TS = MCSI_Data_monthAvg_ts_Y_test,linetype = "TS",Name = "Original Result")

## Put the new line into our plot
Tempplot%>%
  add_lines(x=newline$X,text=newline$TEXT,y=newline$Y,name=newline$NAME,line=list(color="grey"))

TSplotly documentation built on Aug. 2, 2019, 5:04 p.m.