Alert button
Picture for Chainarong Amornbunchornvej

Chainarong Amornbunchornvej

Alert button

Framework for Variable-lag Motif Following Relation Inference In Time Series using Matrix Profile analysis

Jan 05, 2024
Naaek Chinpattanakarn, Chainarong Amornbunchornvej

Viaarxiv icon

Framework for inferring empirical causal graphs from binary data to support multidimensional poverty analysis

May 12, 2022
Chainarong Amornbunchornvej, Navaporn Surasvadi, Anon Plangprasopchok, Suttipong Thajchayapong

Figure 1 for Framework for inferring empirical causal graphs from binary data to support multidimensional poverty analysis
Figure 2 for Framework for inferring empirical causal graphs from binary data to support multidimensional poverty analysis
Figure 3 for Framework for inferring empirical causal graphs from binary data to support multidimensional poverty analysis
Figure 4 for Framework for inferring empirical causal graphs from binary data to support multidimensional poverty analysis
Viaarxiv icon

Mining and modeling complex leadership-followership dynamics of movement data

Oct 04, 2020
Chainarong Amornbunchornvej, Tanya Y. Berger-Wolf

Figure 1 for Mining and modeling complex leadership-followership dynamics of movement data
Figure 2 for Mining and modeling complex leadership-followership dynamics of movement data
Figure 3 for Mining and modeling complex leadership-followership dynamics of movement data
Figure 4 for Mining and modeling complex leadership-followership dynamics of movement data
Viaarxiv icon

Variable-lag Granger Causality and Transfer Entropy for Time Series Analysis

Mar 08, 2020
Chainarong Amornbunchornvej, Elena Zheleva, Tanya Berger-Wolf

Figure 1 for Variable-lag Granger Causality and Transfer Entropy for Time Series Analysis
Figure 2 for Variable-lag Granger Causality and Transfer Entropy for Time Series Analysis
Figure 3 for Variable-lag Granger Causality and Transfer Entropy for Time Series Analysis
Figure 4 for Variable-lag Granger Causality and Transfer Entropy for Time Series Analysis
Viaarxiv icon

Variable-lag Granger Causality for Time Series Analysis

Dec 18, 2019
Chainarong Amornbunchornvej, Elena Zheleva, Tanya Y. Berger-Wolf

Figure 1 for Variable-lag Granger Causality for Time Series Analysis
Figure 2 for Variable-lag Granger Causality for Time Series Analysis
Figure 3 for Variable-lag Granger Causality for Time Series Analysis
Figure 4 for Variable-lag Granger Causality for Time Series Analysis
Viaarxiv icon

A nonparametric framework for inferring orders of categorical data from category-real ordered pairs

Nov 15, 2019
Chainarong Amornbunchornvej, Navaporn Surasvadi, Anon Plangprasopchok, Suttipong Thajchayapong

Figure 1 for A nonparametric framework for inferring orders of categorical data from category-real ordered pairs
Figure 2 for A nonparametric framework for inferring orders of categorical data from category-real ordered pairs
Figure 3 for A nonparametric framework for inferring orders of categorical data from category-real ordered pairs
Figure 4 for A nonparametric framework for inferring orders of categorical data from category-real ordered pairs
Viaarxiv icon

Inferring Coordination Strategies from Time Series of Movement Data

Nov 04, 2019
Chainarong Amornbunchornvej, Tanya Berger-Wolf

Figure 1 for Inferring Coordination Strategies from Time Series of Movement Data
Figure 2 for Inferring Coordination Strategies from Time Series of Movement Data
Figure 3 for Inferring Coordination Strategies from Time Series of Movement Data
Figure 4 for Inferring Coordination Strategies from Time Series of Movement Data
Viaarxiv icon

Identifying Linear Models in Multi-Resolution Population Data using Minimum Description Length Principle to Predict Household Income

Jul 10, 2019
Chainarong Amornbunchornvej, Navaporn Surasvadi, Anon Plangprasopchok, Suttipong Thajchayapong

Figure 1 for Identifying Linear Models in Multi-Resolution Population Data using Minimum Description Length Principle to Predict Household Income
Figure 2 for Identifying Linear Models in Multi-Resolution Population Data using Minimum Description Length Principle to Predict Household Income
Figure 3 for Identifying Linear Models in Multi-Resolution Population Data using Minimum Description Length Principle to Predict Household Income
Figure 4 for Identifying Linear Models in Multi-Resolution Population Data using Minimum Description Length Principle to Predict Household Income
Viaarxiv icon

FLICA: A Framework for Leader Identification in Coordinated Activity

Mar 04, 2016
Chainarong Amornbunchornvej, Ivan Brugere, Ariana Strandburg-Peshkin, Damien Farine, Margaret C. Crofoot, Tanya Y. Berger-Wolf

Figure 1 for FLICA: A Framework for Leader Identification in Coordinated Activity
Figure 2 for FLICA: A Framework for Leader Identification in Coordinated Activity
Figure 3 for FLICA: A Framework for Leader Identification in Coordinated Activity
Figure 4 for FLICA: A Framework for Leader Identification in Coordinated Activity
Viaarxiv icon