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Chapter
Topological Data Analysis for Directed Dependence Networks of Multivariate Time Series Data
Topological data analysis (TDA) approaches are becoming increasingly popular for studying the dependence patterns in multivariate time series data. In particular, various dependence patterns in brain networks ...
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Article
Bayesian parameter inference for partially observed stochastic differential equations driven by fractional Brownian motion
In this paper we consider Bayesian parameter inference for partially observed fractional Brownian motion models. The approach we follow is to time-discretize the hidden process and then to design Markov chain ...
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Article
A Generalized Interrupted Time Series Model for Assessing Complex Health Care Interventions
Assessing the impact of complex interventions on measurable health outcomes is a growing concern in health care and health policy. Interrupted time series (ITS) designs borrow from traditional case-crossover d...
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Article
Open AccessEstimation and probabilistic projection of levels and trends in the sex ratio at birth in seven provinces of Nepal from 1980 to 2050: a Bayesian modeling approach
The sex ratio at birth (SRB; ratio of male to female births) in Nepal has been reported around the normal level on the national level. However, the national SRB could mask the disparity within the country. Giv...
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Article
Clustering Brain Signals: a Robust Approach Using Functional Data Ranking
In this paper, we analyze electroencephalograms (EEGs) which are recordings of brain electrical activity. We develop new clustering methods for identifying synchronized brain regions, where the EEGs show simil...
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Chapter and Conference Paper
Lattice Paths for Persistent Diagrams
Persistent homology has undergone significant development in recent years. However, one outstanding challenge is to build a coherent statistical inference procedure on persistent diagrams. In this paper, we fi...
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Article
Modeling dependence via copula of functionals of Fourier coefficients
The goal of this paper is to develop a measure for characterizing complex dependence between time series that cannot be captured by traditional measures such as correlation and coherence. Our approach is to us...
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Article
Modeling High-Dimensional Multichannel Brain Signals
Our goal is to model and measure functional and effective (directional) connectivity in multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The difficulties from ana...
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Article
Fisher information matrix of binary time series
A common approach to analyzing categorical correlated time series data is to fit a generalized linear model (GLM) with past data as covariate inputs. There remain challenges to conducting inference for time se...
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Article
Modeling Binary Time Series Using Gaussian Processes with Application to Predicting Sleep States
Motivated by the problem of predicting sleep states, we develop a mixed effects model for binary time series with a stochastic component represented by a Gaussian process. The fixed component captures the effe...
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Article
The Hierarchical Spectral Merger Algorithm: A New Time Series Clustering Procedure
We present a new method for time series clustering which we call the Hierarchical Spectral Merger (HSM) method. This procedure is based on the spectral theory of time series and identifies series that share si...
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Article
Open AccessEnsemble-based methods for forecasting census in hospital units
The ability to accurately forecast census counts in hospital departments has considerable implications for hospital resource allocation. In recent years several different methods have been proposed forecasting...
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Article
Patterns of white matter injury in HIV infection after partial immune reconstitution: a DTI tract-based spatial statistics study
HIV-infected individuals with severe immune suppression are more likely to develop HIV-associated neurocognitive disorders than those with preserved immune function. While partial immune reconstitution occurs ...
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Article
Discussion: Time-threshold maps: Using information from wavelet reconstructions with all threshold values simultaneously
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Article
Clinical contributors to cerebral white matter integrity in HIV-infected individuals
HIV-infected people frequently exhibit brain dysfunction characterized by preferential damage to the cerebral white matter. Despite suppressed viral load and reconstituted immune function afforded by combinati...
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Chapter and Conference Paper
Online Analysis of Seismic Signals
Seismic signals can be modeled as non-stationary time series. Methods for analyzing non-stationary time series that have been recently developed are proposed in Adak [1], West, et al. [25] and Ombao, et al. [1...
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Chapter and Conference Paper
Online Analysis of Seismic Signals
Seismic signals can be modeled as non-stationary time series. Methods for analyzing non-stationary time series that have been recently developed are proposed in Adak [1], West, et al. [25] and Ombao, et al. [1...
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Article
The SLEX Model of a Non-Stationary Random Process
We propose a new model for non-stationary random processes to represent time series with a time-varying spectral structure. Our SLEX model can be considered as a discrete time-dependent Cramér spectral represe...
