Open Access. Powered by Scholars. Published by Universities.®
Social and Behavioral Sciences Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Econometrics (7)
- Economics (7)
- Computer Sciences (5)
- Physical Sciences and Mathematics (5)
- Databases and Information Systems (4)
-
- Communication (2)
- Communication Technology and New Media (1)
- Finance (1)
- Income Distribution (1)
- Numerical Analysis and Scientific Computing (1)
- Organizational Communication (1)
- Public Affairs, Public Policy and Public Administration (1)
- Software Engineering (1)
- Transportation (1)
- Urban Studies and Planning (1)
Articles 1 - 11 of 11
Full-Text Articles in Social and Behavioral Sciences
A Panel Clustering Approach To Analyzing Bubble Behavior, Yanbo Liu, Peter C. B. Phillips, Jun Yu
A Panel Clustering Approach To Analyzing Bubble Behavior, Yanbo Liu, Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
This study provides new mechanisms for identifying and estimating explosive bubbles in mixed-root panel autoregressions with a latent group structure. A post-clustering approach is employed that combines a recursive k-means clustering al-gorithm with panel-data test statistics for testing the presence of explosive roots in time series trajectories. Uniform consistency of the k-means clustering algorithm is established, showing that the post-clustering estimate is asymptotically equivalent to the oracle counterpart that uses the true group identities. Based on the estimated group membership, right-tailed self-normalized t-tests and coefficient-based J-tests, each with pivotal limit distributions, are introduced to detect the explosive roots. The usual …
Determining The Number Of Communities In Degree-Corrected Stochastic Block Models, Shujie Ma, Liangjun Su, Yichong Zhang
Determining The Number Of Communities In Degree-Corrected Stochastic Block Models, Shujie Ma, Liangjun Su, Yichong Zhang
Research Collection School Of Economics
We propose to estimate the number of communities in degree-corrected stochastic block models based on a pseudo likelihood ratio. For estimation, we consider a spectral clustering together with binary segmentation method. This approach guarantees an upper bound for the pseudo likelihood ratio statistic when the model is over-fitted. We also derive its limiting distribution when the model is under-fitted. Based on these properties, we establish the consistency of our estimator for the true number of communities. Developing these theoretical properties require a mild condition on the average degree: growing at a rate faster than log(n), where n is the number …
Identifying Latent Group Structures In Nonlinear Panels, Wuyi Wang, Liangjun Su
Identifying Latent Group Structures In Nonlinear Panels, Wuyi Wang, Liangjun Su
Research Collection School Of Economics
We propose a procedure to identify latent group structures in nonlinear panel data models where some regression coefficients are heterogeneous across groups but homogeneous within a group and the group number and membership are unknown. To identify the group structures, we consider the order statistics for the preliminary unconstrained consistent estimators of the regression coefficients and translate the problem of classification into the problem of break detection. Then we extend the sequential binary segmentation algorithm of Bai (1997) for break detection from the time series setup to the panel data framework. We demonstrate that our method is able to identify …
Using Smart Card Data To Model Commuters’ Responses Upon Unexpected Train Delays, Xiancai Tian, Baihua Zheng
Using Smart Card Data To Model Commuters’ Responses Upon Unexpected Train Delays, Xiancai Tian, Baihua Zheng
Research Collection School Of Computing and Information Systems
The mass rapid transit (MRT) network is playing an increasingly important role in Singapore's transit network, thanks to its advantages of higher capacity and faster speed. Unfortunately, due to aging infrastructure, increasing demand, and other reasons like adverse weather condition, commuters in Singapore recently have been facing increasing unexpected train delays (UTDs), which has become a source of frustration for both commuters and operators. Most, if not all, existing works on delay management do not consider commuters' behavior. We dedicate this paper to the study of commuters' behavior during UTDs. We adopt a data-driven approach to analyzing the six-month' real …
Exploiting The Interdependency Of Land Use And Mobility For Urban Planning, Kasthuri Jayarajah, Andrew Tan, Archan Misra
Exploiting The Interdependency Of Land Use And Mobility For Urban Planning, Kasthuri Jayarajah, Andrew Tan, Archan Misra
Research Collection School Of Computing and Information Systems
Urban planners and economists alike have strong interest in understanding the inter-dependency of land use and people flow. The two-pronged problem entails systematic modeling and understanding of how land use impacts crowd flow to an area and in turn, how the influx of people to an area (or lack thereof) can influence the viability of business entities in that area. With cities becoming increasingly sensor-rich, for example, digitized payments for public transportation and constant trajectory tracking of buses and taxis, understanding and modelling crowd flows at the city scale, as well as, at finer granularity such as at the neighborhood …
Homogeneity Pursuit In Panel Data Models: Theory And Application, Wuyi Wang, Peter C. B. Phillips, Liangjun Su
Homogeneity Pursuit In Panel Data Models: Theory And Application, Wuyi Wang, Peter C. B. Phillips, Liangjun Su
Research Collection School Of Economics
This paper studies the estimation of a panel data model with latent structures where individuals can be classified into different groups with the slope parameters being homogeneous within the same group but heterogeneous across groups. To identify the unknown group structure of vector parameters, we design an algorithm called Panel-CARDS. We show that it can identify the true group structure asymptotically and estimate the model parameters consistently at the same time. Simulations evaluate the performance and corroborate the asymptotic theory in several practical design settings. The empirical application reveals the heterogeneous grouping effect of income on democracy.
Identifying Latent Group Structures In Nonlinear Panels, Wuyi Wang, Liangjun Su
Identifying Latent Group Structures In Nonlinear Panels, Wuyi Wang, Liangjun Su
Research Collection School Of Economics
We propose a procedure to identify latent group structures in nonlinear panel data models where some regression coefficients are heterogeneous across groups but homogeneous within a group and the group number and membership are unknown. To identify the group structures, we consider the order statistics for the preliminary unconstrained consistent estimators of the regression coefficients and translate the problem of classification into the problem of break detection. Then we extend the sequential binary segmentation algorithm of Bai (1997) for break detection from the time series setup to the panel data framework. We demonstrate that our method is able to identify …
Strong Consistency Of Spectral Clustering For Stochastic Block Models, Liangjun Su, Wuyi Wang, Yichong Zhang
Strong Consistency Of Spectral Clustering For Stochastic Block Models, Liangjun Su, Wuyi Wang, Yichong Zhang
Research Collection School Of Economics
In this paper we prove the strong consistency of several methods based on thespectral clustering techniques that are widely used to study the communitydetection problem in stochastic block models (SBMs). We show that under someweak conditions on the minimal degree, the number of communities, and theeigenvalues of the probability block matrix, the K-means algorithm applied tothe Eigenvectors of the graph Laplacian associated with its first few largesteigenvalues can classify all individuals into the true community uniformlycorrectly almost surely. Extensions to both regularized spectral clustering anddegree-corrected SBMs are also considered. We illustrate the performance ofdifferent methods on simulated networks.
Homogeneity Pursuit In Panel Data Models: Theory And Applications, Wuyi Wang, Peter C. B. Phillips, Liangjun Su
Homogeneity Pursuit In Panel Data Models: Theory And Applications, Wuyi Wang, Peter C. B. Phillips, Liangjun Su
Research Collection School Of Economics
This paper studies estimation of a panel data model with latent structures where individuals can be classified into different groups where slope parameters are homogeneous within the same group but heterogeneous across groups. To identify the unknown group structure of vector parameters, we design an algorithm called Panel-CARDS which is a systematic extension of the CARDS procedure proposed by Ke, Fan, and Wu (2015) in a cross section framework. The extension addresses the problem of comparing vector coefficients in a panel model for homogeneity and introduces a new concept of controlled classification of multidimensional quantities called the segmentation net. We …
Extracting And Normalizing Entity-Actions From Users' Comments, Swapna Gottipati, Jing Jiang
Extracting And Normalizing Entity-Actions From Users' Comments, Swapna Gottipati, Jing Jiang
Research Collection School Of Computing and Information Systems
With the growing popularity of opinion-rich resources on the Web, new opportunities and challenges arise and aid people in actively using such information to understand the opinions of others. Opinion mining process currently focuses on extracting the sentiments of the users on products, social, political and economical issues. In many instances, users not only express their sentiments but also contribute their ideas, requests and suggestions through comments. Such comments are useful for domain experts and are referred to as actionable content. Extracting actionable knowledge from online social media has attracted a growing interest from both academia and the industry. We …
The Social Network Of Software Engineering Research, Subhajit Datta, Nishant Kumar, Santonu Sarkar
The Social Network Of Software Engineering Research, Subhajit Datta, Nishant Kumar, Santonu Sarkar
Research Collection School Of Computing and Information Systems
The social network perspective has served as a useful framework for studying scientific research collaboration in different disciplines. Although collaboration in computer science research has received some attention, software engineering research collaboration has remained unexplored to a large extent. In this paper, we examine the collaboration networks based on co-authorship information of papers from ten software engineering publication venues over the 1976-2010 time period. We compare time variations of certain parameters of these networks with corresponding parameters of collaboration networks from other disciplines. We also explore whether software engineering collaboration networks manifest symptoms of the small-world phenomenon, conform to the …