Search results for: Kung-Sik Chan

Items from 1 to 20 out of 40 results

article

Conformal Multi‐Target Hyperrectangles

Max Sampson, Kung‐Sik Chan

Statistical Analysis and Data Mining: The ASA Data Science Journal > 17 > 5 > n/a - n/a

We propose conformal hyperrectangular prediction regions for multi‐target regression. We propose split conformal prediction algorithms for both point and quantile regression to form hyperrectangular prediction regions, which allow for easy marginal interpretation and do not require covariance estimation. In practice, it is preferable that a prediction region is balanced, that is, having identical...

article

Random projection ensemble classification with high‐dimensional time series

Fuli Zhang, Kung‐Sik Chan

Biometrics > 79 > 2 > 964 - 974

Multivariate time‐series (MTS) data are prevalent in diverse domains and often high dimensional. We propose new random projection ensemble classifiers with high‐dimensional MTS. The method first applies dimension reduction in the time domain via randomly projecting the time‐series variables into some low‐dimensional space, followed by measuring the disparity via some novel base classifier between...

article

On the Ergodicity of First‐Order Threshold Autoregressive Moving‐Average Processes

Kung‐Sik Chan, Greta Goracci

Journal of Time Series Analysis > 40 > 2 > 256 - 264

We introduce a certain Markovian representation for the threshold autoregressive moving‐average (TARMA) process with which we solve the long‐standing problem regarding the irreducibility condition of a first‐order TARMA model. Under some mild regularity conditions, we obtain a complete classification of the parameter space of an invertible first‐order TARMA model into parametric regions over which...

article

Nitrate transport and supply limitations quantified using high-frequency stream monitoring and turning point analysis

Christopher S. Jones, Bo Wang, Keith E. Schilling, Kung-sik Chan

Journal of Hydrology > 2017 > 549 > C > 581-591

Agricultural landscapes often leak inorganic nitrogen to the stream network, usually in the form of nitrate-nitrite (NO_x-N), degrading downstream water quality on both the local and regional scales. While the spatial distribution of nitrate sources has been delineated in many watersheds, less is known about the complicated temporal dynamics that drive stream NO_x-N because traditional methods of stream...

article

Detection of smoothly distributed spatial outliers, with applications to identifying the distribution of parenchymal hyperinflation following an airway challenge in asthmatics

Andrew L. Thurman, Jiwoong Choi, Sanghun Choi, Ching‐Long Lin, more

Statistics in Medicine > 36 > 10 > 1638 - 1654

Methacholine challenge tests are used to measure changes in pulmonary function that indicate symptoms of asthma. In addition to pulmonary function tests, which measure global changes in pulmonary function, computed tomography images taken at full inspiration before and after administration of methacholine provide local air volume changes (hyper‐inflation post methacholine) at individual acinar units,...

article

An integrated K-means – Laplacian cluster ensemble approach for document datasets

Sen Xu, Kung-Sik Chan, Jun Gao, Xiufang Xu, more

Neurocomputing > 2016 > 214 > C > 495-507

Cluster ensemble has become an important extension to traditional clustering algorithms, yet the cluster ensemble problem is very challenging due to the inherent difficulty in resolving the label correspondence problem. We adapted the integrated K-means – Laplacian clustering approach to solve the cluster ensemble problem by exploiting both the attribute information embedded in the cluster labels...

article

Novel Logistic Regression Model of Chest CT Attenuation Coefficient Distributions for the Automated Detection of Abnormal (Emphysema or ILD) Versus Normal Lung

Kung-Sik Chan, Feiran Jiao, Marek A. Mikulski, Alicia Gerke, more

Academic Radiology > 2016 > 23 > 3 > 304-314

We evaluated the role of automated quantitative computed tomography (CT) scan interpretation algorithm in detecting interstitial lung disease (ILD) and/or emphysema in a sample of elderly subjects with mild lung disease. We hypothesized that the quantification and distributions of CT attenuation values on lung CT, over a subset of Hounsfield units (HUs) range (−1000 HU, 0 HU), can differentiate early...

article

Assessing the Relative Importance of Nitrogen-Retention Processes in a Large Reservoir Using Time-Series Modeling

Elizabeth Hansen, Kung-Sik Chan, Christopher S. Jones, Keith Schilling

Journal of Agricultural, Biological and Environmental Statistics > 2016 > 21 > 1 > 152-169

Nitrogen (N) removal within reservoirs can be substantial, but few studies have reported the relative importance of various N-retention pathways. Assessing N-removal processes in reservoirs is important for quantifying the impacts of reservoirs on downstream water quality. In this study, we used a time-series approach to quantify the relative importance of various N-removal processes in the Saylorville...

article

Quasi-likelihood estimation of a threshold diffusion process

Fei Su, Kung-Sik Chan

Journal of Econometrics > 2015 > 189 > 2 > 473-484

The threshold diffusion process, first introduced by Tong (1990), is a continuous-time process satisfying a stochastic differential equation with a piecewise linear drift term and a piecewise smooth diffusion term, e.g., a piecewise constant function or a piecewise power function. We consider the problem of estimating the (drift) parameters indexing the drift term of a threshold diffusion process...

article

A note on rank reduction in sparse multivariate regression

Kun Chen, Kung-Sik Chan

Journal of Statistical Theory and Practice > 2016 > 10 > 1 > 100-120

A reduced-rank regression with sparse singular value decomposition (RSSVD) approach was proposed by Chen et al. for conducting variable selection in a reduced-rank model. To jointly model the multivariate response, the method efficiently constructs a prespecified number of latent variables as some sparse linear combinations of the predictors. Here, we generalize the method to also perform rank reduction,...

article

Additive models with spatio-temporal data

Xiangming Fang, Kung-Sik Chan

Environmental and Ecological Statistics > 2015 > 22 > 1 > 61-86

Additive models (AMs) have been widely used in environmental, biological, and ecological studies. While the procedure for fitting an AM to independent data has been well established, the currently available methods for fitting AMs with correlated data are not completely satisfactory in practice. We propose a new approach based on penalized likelihood method to fit AMs for spatio-temporal data. Both...

article

An approach for modeling cross-immunity of two strains, with application to variants of Bartonella in terms of genetic similarity

Kwang Woo Ahn, Michael Kosoy, Kung-Sik Chan

Epidemics > 2014 > 7 > Complete > 7-12

We developed a two-strain susceptible-infected-recovered (SIR) model that provides a framework for inferring the cross-immunity between two strains of a bacterial species in the host population with discretely sampled co-infection time-series data. Moreover, the model accounts for seasonality in host reproduction. We illustrate an approach using a dataset describing co-infections by several strains...

article

A distribution-free test for anomalous gamma-ray spectra

Kung-sik Chan, Jinzheng Li, William Eichinger, Er-Wei Bai

Radiation Measurements > 2014 > 63 > Complete > 18-25

Gamma-ray spectra are increasingly acquired in monitoring cross-border traffic, or in an area search for lost or orphan special nuclear material (SNM). The signal in such data is generally weak, resulting in poorly resolved spectra, thereby making it hard to detect the presence of SNM. We develop a new test for detecting anomalous spectra by characterizing the complete shape change in a spectrum from...

article

Approximate conditional least squares estimation of a nonlinear state-space model via an unscented Kalman filter

Kwang Woo Ahn, Kung-Sik Chan

Computational Statistics and Data Analysis > 2014 > 69 > Complete > 243-254

The problem of estimating a nonlinear state-space model whose state process is driven by an ordinary differential equation (ODE) or a stochastic differential equation (SDE), with discrete-time data is studied. A new estimation method is proposed based on minimizing the conditional least squares (CLS) with the conditional mean function computed approximately via the unscented Kalman filter (UKF). Conditions...

article

A robust method for detecting nuclear materials when the underlying model is inexact

Paul Kump, Er-Wei Bai, Kung-sik Chan, William Eichinger

Radiation Measurements > 2013 > 59 > Complete > 144-150

This paper is concerned with the detection and identification of nuclides from weak and poorly resolved gamma-ray energy spectra when the underlying model is not known exactly. The algorithm proposed and tested here pairs an exciting and relatively new model selection algorithm with the method of total least squares. Gamma-ray counts are modeled as Poisson processes where the average part is taken...

article

On the convergence rate of the unscented transformation

Kwang Woo Ahn, Kung-Sik Chan

Annals of the Institute of Statistical Mathematics > 2013 > 65 > 5 > 889-912

Nonlinear state-space models driven by differential equations have been widely used in science. Their statistical inference generally requires computing the mean and covariance matrix of some nonlinear function of the state variables, which can be done in several ways. For example, such computations may be approximately done by Monte Carlo, which is rather computationally expensive. Linear approximation...

article

Detection of shielded radionuclides from weak and poorly resolved spectra using group positive RIVAL

Paul Kump, Er-Wei Bai, Kung-Sik Chan, William Eichinger

Radiation Measurements > 2013 > 48 > Complete > 18-28

This paper is concerned with the identification of nuclides from weak and poorly resolved spectra in the presence of unknown radiation shielding materials such as carbon, water, concrete and lead. Since a shield will attenuate lower energies more so than higher ones, isotope sub-spectra must be introduced into models and into detection algorithms. We propose a new algorithm for detection, called group...

article

Dynamic regression modeling of daily nitrate-nitrogen concentrations in a large agricultural watershed

Zhujing Feng, Keith E. Schilling, Kung-Sik Chan

Environmental Monitoring and Assessment > 2013 > 185 > 6 > 4605-4617

Nitrate-nitrogen concentrations in rivers represent challenges for water supplies that use surface water sources. Nitrate concentrations are often modeled using time-series approaches, but previous efforts have typically relied on monthly time steps. In this study, we developed a dynamic regression model of daily nitrate concentrations in the Raccoon River, Iowa, that incorporated contemporaneous...

article

Variable selection via RIVAL (removing irrelevant variables amidst Lasso iterations) and its application to nuclear material detection

Paul Kump, Er-Wei Bai, Kung-sik Chan, Bill Eichinger, more

Automatica > 2012 > 48 > 9 > 2107-2115

In many situations, the number of data points is fixed, and the asymptotic convergence results of popular model selection tools may not be useful. A new algorithm for model selection, RIVAL (removing irrelevant variables amidst Lasso iterations), is presented and shown to be particularly effective for a large but fixed number of data points. The algorithm is motivated by an application of nuclear...

article

Bartonella bacteria in nature: Where does population variability end and a species start?

Michael Kosoy, David T.S. Hayman, Kung-Sik Chan

Infection, Genetics and Evolution > 2012 > 12 > 5 > 894-904

The application of new molecular approaches has permitted the differentiation of numerous strains belonging to the genus Bartonella and identification of new Bartonella species. However, the molecular typing of these organisms should be coupled with studies aimed at defining the biological properties of the newly described species. The long-history of co-adaptation between bartonella1Bartonella species...

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INFONA - science communication portal

Search results for: Kung-Sik Chan

Conformal Multi‐Target Hyperrectangles

Random projection ensemble classification with high‐dimensional time series

On the Ergodicity of First‐Order Threshold Autoregressive Moving‐Average Processes

Nitrate transport and supply limitations quantified using high-frequency stream monitoring and turning point analysis

Detection of smoothly distributed spatial outliers, with applications to identifying the distribution of parenchymal hyperinflation following an airway challenge in asthmatics

An integrated K-means – Laplacian cluster ensemble approach for document datasets

Novel Logistic Regression Model of Chest CT Attenuation Coefficient Distributions for the Automated Detection of Abnormal (Emphysema or ILD) Versus Normal Lung

Assessing the Relative Importance of Nitrogen-Retention Processes in a Large Reservoir Using Time-Series Modeling

Quasi-likelihood estimation of a threshold diffusion process

A note on rank reduction in sparse multivariate regression

Additive models with spatio-temporal data

An approach for modeling cross-immunity of two strains, with application to variants of Bartonella in terms of genetic similarity

A distribution-free test for anomalous gamma-ray spectra

Approximate conditional least squares estimation of a nonlinear state-space model via an unscented Kalman filter

A robust method for detecting nuclear materials when the underlying model is inexact

On the convergence rate of the unscented transformation

Detection of shielded radionuclides from weak and poorly resolved spectra using group positive RIVAL

Dynamic regression modeling of daily nitrate-nitrogen concentrations in a large agricultural watershed

Variable selection via RIVAL (removing irrelevant variables amidst Lasso iterations) and its application to nuclear material detection

Bartonella bacteria in nature: Where does population variability end and a species start?

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