GetPIPs: Retrieve Perceptually Important Points (PIPS) from a Time...

In joshmarsh/TSPatternQuery: A Time Series Pattern Query Tool Using PIPs and Hybrid Template-Ruleset Matching

Description

Perceptually Important Points (PIPs) are points that are perceptually important for the identification of patterns in time series data. Each PIP is identified in this function by choosing the point with the maximum perpendicular distance to a line drawn between adjacent PIPs. Endpoints of the time series are chosen as the first PIPS, and the process is repeated iteratively until the desired number of PIPs are found.

Usage

GetPIPs(timeseries, num.pips)

Arguments

timeseries	The xts time series within which PIPs will be identified
num.pips	A numeric for the number of PIPs to be identified

Value

An xts time series containing the pips from the timeseries provided

References

Zhe Zhang, Jian Jiang, Xiaoyan Liu, Ricky Lau, Huaiqing Wang, and Rui Zhang. A real time hybrid pattern matching scheme for stock time series. In Proceedings of the Twenty-First Australasian Conference on Database Technologies - Volume 104, ADC ’10, pages 161–170, Darlinghurst, Australia, Australia, 2010. Australian Computer Society, Inc.

joshmarsh/TSPatternQuery documentation built on May 19, 2019, 8:53 p.m.