TimeSeriesAnalysis: TimeSeriesAnalysis

In grieman/grieman:

Description

Detects and marks outliers, breakpoints, and changes in variance in a time series.

Usage

TimeSeriesAnalysis(valuecol, datecol, plot = TRUE, plotly = FALSE,
  IQRs = 2)

Arguments

valuecol	Data vector
datecol	Date vector
plot	toggles drawing of plot
plotly	toggles plotting in plotly or ggplot
IQRs	Allowable number of IQRs' away from the first or third quartile for a point to not be considered an outlier. Higher numbers result in fewer outliers.

Value

a data frame with the times, data values, outliers, changes in mean, and changes in variance

Examples

data <- c(rnorm(50,0,1), rnorm(50,0,2),20,rnorm(50,10,1))
dates <- seq(as.Date("2016/1/1"), by="days", length.out=151)
TimeSeriesAnalysis(data,dates)

TimeSeriesAnalysis(c(1,2,3,5,-10,4,2,4,2,6,8,9), seq(as.Date("2016/1/1"), by="days", length.out=12))

grieman/grieman documentation built on May 17, 2019, 8:36 a.m.