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Articles 1 - 5 of 5
Full-Text Articles in Longitudinal Data Analysis and Time Series
Forecasting Of The Covid-19 Epidemic: A Scientometric Analysis, Pandri Ferdias, Ansari Saleh Ahmar
Forecasting Of The Covid-19 Epidemic: A Scientometric Analysis, Pandri Ferdias, Ansari Saleh Ahmar
Library Philosophy and Practice (e-journal)
This study presented a scientometric analysis of scientific publications with discussions of forecasting and COVID-19. The data of this study were obtained from the Scopus database using the keywords: ( TITLE-ABS-KEY (forecast) AND TITLE-ABS-KEY (covid)) and the data were taken on March 26, 2021. This study was a scientometric study. The data were subsequently analyzed using the VosViewer and Bibliometrix R Package. The results showed that “COVID-19” was the keyword most frequently used by researchers, followed by “forecasting” and “human”. Authors who discussed the topic of forecasting COVID-19 come from 83 different countries/regions, with the most articles sent by authors …
Role Of Misclassification Estimates In Estimating Disease Prevalence And A Non-Linear Approach To Study Synchrony Using Heart Rate Variability In Chickens, Dola Pathak
Department of Statistics: Dissertations, Theses, and Student Work
Infectious disease assays can be imperfect. When estimating disease prevalence, these imperfections are accounted for by incorporating assay sensitivity and specificity into point and variance estimates. Unfortunately, these accuracy measures are often treated as fixed constants, rather than acknowledging that they are estimates from an assay validation process. The purpose of this study is to show the detrimental effect of not taking into account this sampling variability when samples are obtained through group testing (aka, pooled testing). We show that confidence interval coverage can dramatically decline as the sample size increases for the main sample of interest. As a remedy …
A New Approach To Modeling Multivariate Time Series On Multiple Temporal Scales, Tucker Zeleny
A New Approach To Modeling Multivariate Time Series On Multiple Temporal Scales, Tucker Zeleny
Department of Statistics: Dissertations, Theses, and Student Work
In certain situations, observations are collected on a multivariate time series at a certain temporal scale. However, there may also exist underlying time series behavior on a larger temporal scale that is of interest. Often times, identifying the behavior of the data over the course of the larger scale is the key objective. Because this large scale trend is not being directly observed, describing the trends of the data on this scale can be more difficult. To further complicate matters, the observed data on the smaller time scale may be unevenly spaced from one larger scale time point to the …
Sequence Comparison And Stochastic Model Based On Multi-Order Markov Models, Xiang Fang
Sequence Comparison And Stochastic Model Based On Multi-Order Markov Models, Xiang Fang
Department of Statistics: Dissertations, Theses, and Student Work
This dissertation presents two statistical methodologies developed on multi-order Markov models. First, we introduce an alignment-free sequence comparison method, which represents a sequence using a multi-order transition matrix (MTM). The MTM contains information of multi-order dependencies and provides a comprehensive representation of the heterogeneous composition within a sequence. Based on the MTM, a distance measure is developed for pair-wise comparison of sequences. The new method is compared with the traditional maximum likelihood (ML) method, the complete composition vector (CCV) method and the improved version of the complete composition vector (ICCV) method using simulated sequences. We further illustrate the application of …
The Time Invariance Principle, Ecological (Non)Chaos, And A Fundamental Pitfall Of Discrete Modeling, Bo Deng
The Time Invariance Principle, Ecological (Non)Chaos, And A Fundamental Pitfall Of Discrete Modeling, Bo Deng
Department of Mathematics: Faculty Publications
This paper is to show that most discrete models used for population dynamics in ecology are inherently pathological that their predications cannot be independently verified by experiments because they violate a fundamental principle of physics. The result is used to tackle an on-going controversy regarding ecological chaos. Another implication of the result is that all continuous dynamical systems must be modeled by differential equations. As a result it suggests that researches based on discrete modeling must be closely scrutinized and the teaching of calculus and differential equations must be emphasized for students of biology.