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Longitudinal Data Analysis and Time Series Commons™
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Articles 1 - 21 of 21
Full-Text Articles in Longitudinal Data Analysis and Time Series
Online Detection Of Outliers And Structural Breaks Using Sequential Monte Carlo Methods, Richard Wanjohi
Online Detection Of Outliers And Structural Breaks Using Sequential Monte Carlo Methods, Richard Wanjohi
Graduate Theses and Dissertations
Outliers and structural breaks occur quite frequently in time series data. Whereas outliers often contain valuable information
about the process under study, they are known to have serious negative impact on statistical data analysis. Most obvious effect is model misspecification and biased parameter estimation which results in wrong conclusions and inaccurate predictions. Structural time series consist of underlying features such as level, slope, cycles or seasonal components. Structural breaks are permanent disruptions of one or more of these components and might be a signal of serious changes in the observed process.
Detecting outliers and estimating the location of structural breaks …
Estimating Effective Connectivity From Fmri Data Using Factor-Based Subspace Autoregressive Models, Chee-Ming Ting Phd, Abd-Krim Seghouane Phd, Sh-Hussain Salleh Phd, Alias M. Noor Phd
Estimating Effective Connectivity From Fmri Data Using Factor-Based Subspace Autoregressive Models, Chee-Ming Ting Phd, Abd-Krim Seghouane Phd, Sh-Hussain Salleh Phd, Alias M. Noor Phd
Chee-Ming Ting
Spatiotemporal Crime Analysis, James Q. Tay, Abish Malik, Sherry Towers, David Ebert
Spatiotemporal Crime Analysis, James Q. Tay, Abish Malik, Sherry Towers, David Ebert
The Summer Undergraduate Research Fellowship (SURF) Symposium
There has been a rise in the use of visual analytic techniques to create interactive predictive environments in a range of different applications. These tools help the user sift through massive amounts of data, presenting most useful results in a visual context and enabling the person to rapidly form proactive strategies. In this paper, we present one such visual analytic environment that uses historical crime data to predict future occurrences of crimes, both geographically and temporally. Due to the complexity of this analysis, it is necessary to find an appropriate statistical method for correlative analysis of spatiotemporal data, as well …
Predicting High-Stakes Tests Of Math Achievement Using A Group-Administered Rti Instrument: Validating Skills Measured By The Monitoring Instructional Responsiveness: Math, Jeremy Thomas Coles
Predicting High-Stakes Tests Of Math Achievement Using A Group-Administered Rti Instrument: Validating Skills Measured By The Monitoring Instructional Responsiveness: Math, Jeremy Thomas Coles
Doctoral Dissertations
Three universal screeners and nine progress monitoring probes from the Monitoring Instructional Responsiveness: Math (MIR:M), a silent, group-administered math assessment designed for implementation with an RTI Model, were administered to 223 fifth-grade students. The growth parameters of the overall MIR:M composite and two global composites (math calculation and math reasoning) identified significant variation in student growth, within significant linear and quadratic trajectories. However, there were significant differences in the nature of the growth trajectories that have applied educational implications. In addition, growth parameters across the three composites provided significant predictive potential when using the Tennessee Comprehensive Assessment Program (TCAP) Achievement …
Genetic Predictors Of Metabolic Side Effects Of Diuretic Therapy, Jorge L. Del Aguila
Genetic Predictors Of Metabolic Side Effects Of Diuretic Therapy, Jorge L. Del Aguila
Dissertations & Theses (Open Access)
Thiazide diuretics are a recommended first-line monotherapy for hypertension (i.e.SBP>140 mmHg or DBP>90 mmHg). Even so, diuretics are associated with adverse metabolic side effects, such as hyperlipidemia, hyperglycemia and hypokalemia which increase the risk of developing type II diabetes. This thesis used three analytical strategies to identify and quantify genetic factors that contribute to the development of adverse metabolic effects due to thiazide diuretic treatment. I performed a genome-wide association study (GWAS) and meta-analysis of the change in fasting plasma glucose and triglycerides in response to HCTZ from two different clinical trials: the Pharmacogenomic Evaluation of Antihypertensive Responses …
Estimation Of High-Dimensional Brain Connectivity From Fmri Data Using Factor Modeling, Chee-Ming Ting Phd, Abd-Krim Seghouane, Sh-Hussain Salleh, Alias M. Noor
Estimation Of High-Dimensional Brain Connectivity From Fmri Data Using Factor Modeling, Chee-Ming Ting Phd, Abd-Krim Seghouane, Sh-Hussain Salleh, Alias M. Noor
Chee-Ming Ting
We consider identifying effective connectivity of brain networks from fMRI time series. The standard vector autoregressive (VAR) models fail to give reliable network estimates, typically involving very large number of nodes. This paper adopts a dimensionality reduction approach based on factor modeling, to enable effective and efficient high-dimensional VAR analysis of large network connectivity. We derive a subspace VAR (SVAR) model from the factor model (FM) in which the observations are driven by a lower dimensional subspace of common latent factors, following an autoregressive dynamics. We consider the principal components (PC) method which can produce consistent estimators for the FM, …
Time Trends And Predictors Of Initiation For Cigarette And Waterpipe Smoking Among Jordanian School Children: Irbid, 2008-2011, Karma L. Mckelvey Phd
Time Trends And Predictors Of Initiation For Cigarette And Waterpipe Smoking Among Jordanian School Children: Irbid, 2008-2011, Karma L. Mckelvey Phd
FIU Electronic Theses and Dissertations
Smoking prevalence among adolescents in the Middle East remains high while rates of smoking have been declining among adolescents elsewhere. The aims of this research were to (1) describe patterns of cigarette and waterpipe (WP) smoking, (2) identify determinants of WP smoking initiation, and (3) identify determinants of cigarette smoking initiation in a cohort of Jordanian school children.
Among this cohort of school children in Irbid, Jordan, (age ≈ 12.6 at baseline) the first aim (N=1,781) described time trends in smoking behavior, age at initiation, and changes in frequency of smoking from 2008-2011 (grades 7 – 10). The second aim …
Time Series Decomposition Using Singular Spectrum Analysis, Cheng Deng
Time Series Decomposition Using Singular Spectrum Analysis, Cheng Deng
Electronic Theses and Dissertations
Singular Spectrum Analysis (SSA) is a method for decomposing and forecasting time series that recently has had major developments but it is not yet routinely included in introductory time series courses. An international conference on the topic was held in Beijing in 2012. The basic SSA method decomposes a time series into trend, seasonal component and noise. However there are other more advanced extensions and applications of the method such as change-point detection or the treatment of multivariate time series. The purpose of this work is to understand the basic SSA method through its application to the monthly average sea …
A Stochastic Parameter Regression Model For Long Memory Time Series, Rose Marie Ocker
A Stochastic Parameter Regression Model For Long Memory Time Series, Rose Marie Ocker
Boise State University Theses and Dissertations
In a complex and dynamic world, the assumption that relationships in a system remain constant is not necessarily a well-founded one. Allowing for time-varying parameters in a regression model has become a popular technique, but the best way to estimate the parameters of the time-varying model is still in discussion. These parameters can be autocorrelated with their past for a long time (long memory), but most of the existing models for parameters are of the short memory type, leaving the error process to account for any long memory behavior in the response variable. As an alternative, we propose a long …
High Frequency Data: Modeling Durations Via The Acd And Log Acd Models, Lilian Cheung
High Frequency Data: Modeling Durations Via The Acd And Log Acd Models, Lilian Cheung
Honors Scholar Theses
This thesis proposes a method of finding initial parameter estimates in the Log ACD1 model for use in recursive estimation. The recursive estimating equations method is applied to the Log ACD1 model to find recursive estimates for the unknown parameters in the model. A literature review is provided on the ACD and Log ACD models, and on the theory of estimating equations. Monte Carlo simulations indicate that the proposed method of finding initial parameter estimates is viable. The parameter estimation process is demonstrated by fitting an ACD model and a Log ACD model to a set of IBM …
The Modified R A Robust Measure Of Association For Time Series, Muhammad Irfan Malik
The Modified R A Robust Measure Of Association For Time Series, Muhammad Irfan Malik
irfan.phdet24@iiu.edu.pk
Since times of Yule (1926), it is known that correlation between two time series can produce spurious results. Granger and Newbold (1974) see the roots of spurious correlation in non-stationarity of the time series. However the study of Granger, Hyung and Jeon (2001) prove that spurious correlation also exists in stationary time series. These facts make the correlation coefficient an unreliable measure of association. This paper proposes ‘Modified R’ as an alternate measure of association for the time series. The Modified R is robust to the type of stationarity and type of deterministic part in the time series. The performance …
Statistical Methods For The Analysis Of Rna Sequencing Data, Man-Kee Maggie Chu
Statistical Methods For The Analysis Of Rna Sequencing Data, Man-Kee Maggie Chu
Electronic Thesis and Dissertation Repository
The next generation sequencing technology, RNA-sequencing (RNA-seq), has an increasing popularity over traditional microarrays in transcriptome analyses. Statistical methods used for gene expression analyses with these two technologies are different because the array-based technology measures intensities using continuous distributions, whereas RNA-seq provides absolute quantification of gene expression using counts of reads. There is a need for reliable statistical methods to exploit the information from the rapidly evolving sequencing technologies and limited work has been done on expression analysis of time-course RNA-seq data. In this dissertation, we propose a model-based clustering method for identifying gene expression patterns in time-course RNA-seq data. …
Mediation Analysis With Time-Varying Exposures And Mediators, Tyler J. Vanderweele, Eric Tchetgen Tchetgen
Mediation Analysis With Time-Varying Exposures And Mediators, Tyler J. Vanderweele, Eric Tchetgen Tchetgen
Harvard University Biostatistics Working Paper Series
In this paper we consider mediation analysis when exposures and mediators vary over time. We give non-parametric identification results, discuss parametric implementation, and also provide a weighting approach to direct and indirect effects based on combining the results of two marginal structural models. We also discuss how our results give rise to a causal interpretation of the effect estimates produced from longitudinal structural equation models. When there are no time-varying confounders affected by prior exposure and mediator values, identification of direct and indirect effects is achieved by a longitudinal version of Pearl's mediation formula. When there are time-varying confounders affected …
Natural Phenomena As Potential Influence On Social And Political Behavior: The Earth’S Magnetic Field, Jackie R. East
Natural Phenomena As Potential Influence On Social And Political Behavior: The Earth’S Magnetic Field, Jackie R. East
Theses and Dissertations--Political Science
Researchers use natural phenomena in a number of disciplines to help explain human behavioral outcomes. Research regarding the potential effects of magnetic fields on animal and human behavior indicates that fields could influence outcomes of interest to social scientists. Tests so far have been limited in scope. This work is a preliminary evaluation of whether the earth’s magnetic field influences human behavior it examines the baseline relationship exhibited between geomagnetic readings and a host of social and political outcomes. The emphasis on breadth of topical coverage in these statistical trials, rather than on depth of development for any one model, …
On Likelihood Ratio Tests When Nuisance Parameters Are Present Only Under The Alternative, Cz Di, K-Y Liang
On Likelihood Ratio Tests When Nuisance Parameters Are Present Only Under The Alternative, Cz Di, K-Y Liang
Chongzhi Di
In parametric models, when one or more parameters disappear under the null hypothesis, the likelihood ratio test statistic does not converge to chi-square distributions. Rather, its limiting distribution is shown to be equivalent to that of the supremum of a squared Gaussian process. However, the limiting distribution is analytically intractable for most of examples, and approximation or simulation based methods must be used to calculate the p values. In this article, we investigate conditions under which the asymptotic distributions have analytically tractable forms, based on the principal component decomposition of Gaussian processes. When these conditions are not satisfied, the principal …
Set-Based Tests For Genetic Association In Longitudinal Studies, Zihuai He, Min Zhang, Seunggeun Lee, Jennifer A. Smith, Xiuqing Guo, Walter Palmas, Sharon L.R. Kardia, Ana V. Diez Roux, Bhramar Mukherjee
Set-Based Tests For Genetic Association In Longitudinal Studies, Zihuai He, Min Zhang, Seunggeun Lee, Jennifer A. Smith, Xiuqing Guo, Walter Palmas, Sharon L.R. Kardia, Ana V. Diez Roux, Bhramar Mukherjee
The University of Michigan Department of Biostatistics Working Paper Series
Genetic association studies with longitudinal markers of chronic diseases (e.g., blood pressure, body mass index) provide a valuable opportunity to explore how genetic variants affect traits over time by utilizing the full trajectory of longitudinal outcomes. Since these traits are likely influenced by the joint effect of multiple variants in a gene, a joint analysis of these variants considering linkage disequilibrium (LD) may help to explain additional phenotypic variation. In this article, we propose a longitudinal genetic random field model (LGRF), to test the association between a phenotype measured repeatedly during the course of an observational study and a set …
Garma Toolbox For Matlab, Mehdi Jalalpour
Testing Longitudinal Data By Logarithmic Quantiles, Manfred Denker, Lucia Tabacu
Testing Longitudinal Data By Logarithmic Quantiles, Manfred Denker, Lucia Tabacu
Mathematics & Statistics Faculty Publications
The shoulder tip pain study of Lumley [13] is re-investigated. It is shown that the new logarithmic quantile estimation (LQE) technique in [9] applies and behaves well under singular covariance structure and small sample sizes as in the shoulder tip pain study. The findings in [6] can be assured under weaker assumptions using a combination of LQE and an ANOVA type statistic. © 2014, Institute of Mathematical Statistics.
Modelling And Analysis On Noisy Financial Time Series, Jinsong Leng
Modelling And Analysis On Noisy Financial Time Series, Jinsong Leng
Research outputs 2014 to 2021
Building the prediction model(s) from the historical time series has attracted many researchers in last few decades. For example, the traders of hedge funds and experts in agriculture are demanding the precise models to make the prediction of the possible trends and cycles. Even though many statistical or machine learning (ML) models have been proposed, however, there are no universal solutions available to resolve such particular prob-lem. In this paper, the powerful forward-backward non-linear filter and wavelet-based denoising method are introduced to remove the high level of noise embedded in financial time series. With the filtered time series, the statistical …
Repeat Sales House Price Index Methodology, Chaitra Nagaraja, Lawrence Brown, Susan Wachter
Repeat Sales House Price Index Methodology, Chaitra Nagaraja, Lawrence Brown, Susan Wachter
Chaitra H Nagaraja
No abstract provided.
Spectral Density Shrinkage For High-Dimensional Time Series, Mark Fiecas, Rainer Von Sachs
Spectral Density Shrinkage For High-Dimensional Time Series, Mark Fiecas, Rainer Von Sachs
Mark Fiecas