Clustering approach for slope change detection in trended data

Mario Beruvides; Víctor G. Tercero-Gómez; María Del Carmen Temblador; Alberto A. Hernández-Luna

Clustering approach for slope change detection in trended data

Mario Beruvides, Víctor G. Tercero-Gómez, María Del Carmen Temblador, Alberto A. Hernández-Luna

Industrial Engineering

Research output: Contribution to conference › Paper › peer-review

Abstract

Most traditional statistical tools have been developed under the assumption of zero slope behavior over time and normally distributed data. However, living systems are systems that tend to have non-normal behavior, exhibit a pattern of constant growth or a steady decrement, and achieve states of dynamic equilibrium, making them hard to manage. This paper evaluates the feasibility of the clustering technique with the median test to estimate slope change points in control charts for data with defined trend with normal and non-normal behavior. A conceptual model is proposed and its implications are discussed.

Original language	English
State	Published - 2010
Event	IIE Annual Conference and Expo 2010 - Cancun, Mexico Duration: Jun 5 2010 → Jun 9 2010

Conference

Conference	IIE Annual Conference and Expo 2010
Country/Territory	Mexico
City	Cancun
Period	06/5/10 → 06/9/10

Keywords

Trend control change point analysis

Cite this

@conference{ec2adcfc588f4c76b6565972707475cb,

title = "Clustering approach for slope change detection in trended data",

abstract = "Most traditional statistical tools have been developed under the assumption of zero slope behavior over time and normally distributed data. However, living systems are systems that tend to have non-normal behavior, exhibit a pattern of constant growth or a steady decrement, and achieve states of dynamic equilibrium, making them hard to manage. This paper evaluates the feasibility of the clustering technique with the median test to estimate slope change points in control charts for data with defined trend with normal and non-normal behavior. A conceptual model is proposed and its implications are discussed.",

keywords = "Trend control change point analysis",

author = "Mario Beruvides and Tercero-G{\'o}mez, {V{\'i}ctor G.} and {Del Carmen Temblador}, Mar{\'i}a and Hern{\'a}ndez-Luna, {Alberto A.}",

year = "2010",

language = "English",

note = "null ; Conference date: 05-06-2010 Through 09-06-2010",

}

TY - CONF

T1 - Clustering approach for slope change detection in trended data

AU - Beruvides, Mario

AU - Tercero-Gómez, Víctor G.

AU - Del Carmen Temblador, María

AU - Hernández-Luna, Alberto A.

PY - 2010

Y1 - 2010

N2 - Most traditional statistical tools have been developed under the assumption of zero slope behavior over time and normally distributed data. However, living systems are systems that tend to have non-normal behavior, exhibit a pattern of constant growth or a steady decrement, and achieve states of dynamic equilibrium, making them hard to manage. This paper evaluates the feasibility of the clustering technique with the median test to estimate slope change points in control charts for data with defined trend with normal and non-normal behavior. A conceptual model is proposed and its implications are discussed.

AB - Most traditional statistical tools have been developed under the assumption of zero slope behavior over time and normally distributed data. However, living systems are systems that tend to have non-normal behavior, exhibit a pattern of constant growth or a steady decrement, and achieve states of dynamic equilibrium, making them hard to manage. This paper evaluates the feasibility of the clustering technique with the median test to estimate slope change points in control charts for data with defined trend with normal and non-normal behavior. A conceptual model is proposed and its implications are discussed.

KW - Trend control change point analysis

UR - http://www.scopus.com/inward/record.url?scp=84901036092&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:84901036092

Y2 - 5 June 2010 through 9 June 2010

ER -

Clustering approach for slope change detection in trended data

Abstract

Conference

Keywords

Other files and links

Fingerprint

Cite this