Physical Sciences and Mathematics Commons^™

Copula-Based Models For Bivariate And Multivariate Zero-Inflated Count Time Series Data, Dimuthu Fernando, Norou Diawara

College of Sciences Posters

Count time series data have multiple applications. The applications can be found in areas of finance, climate, public health and crime data analyses. In some scenarios, count time series come as multivariate vectors that exhibit not only serial dependence within each time series but also with cross correlation among the series. When considering these observed counts, analysis presents crucial challenges when a value, say zero, occurs more often than usual. There is presence of zero-inflation in the data.

In this presentation, we mainly focus on modeling bivariate zero-inflated count time series model based on a joint distribution of the two …

A Bootstrap Test For Informative Intra-Cluster Group Sizes In Clustered Data, Hasika K. Wickrama Senevirathne, Sandipan Dutta

College of Sciences Posters

Clustered data are frequently observed in various domains of scientific and social studies. In a typical clustered data, units within a cluster are correlated while units between different clusters are independent. An example of such clustered data can be found in dental studies where individuals are treated as clusters and the teeth in an individual are the units within a cluster. While analyzing such clustered data, it has been observed that the number of units present in a cluster can be informative in terms of being associated with the outcome from that cluster. Specifically, when the aim is to compare …

Empirically Adjusted Weighted Ordered P-Values Method, Wimarsha Jayanetti, Sinjini Sikdar, N. Rao Chaganty

College of Sciences Posters

Recent advancements in high-throughput technologies have enabled simultaneous inference of thousands of genes. With the abundance of public databases, it is now possible to rapidly access the results of several genomic studies, each of which includes the significance testing results of a large number of genes. Researchers frequently aggregate genomic data from multiple studies in the form of a meta-analysis. Most traditional meta-analysis methods aim at combining summary results to find signals in at least one of the studies. However, often the goal is to identify genes that are differentially expressed in a consistent pattern across multiple studies. Recently, a …

D-Vine Copula Model For Dependent Binary Data, Huihui Lin, N. Rao Chaganty

College of Sciences Posters

High-dimensional dependent binary data are prevalent in a wide range of scientific disciplines. A popular method for analyzing such data is the Multivariate Probit (MP) model. But the MP model sometimes fails even within a feasible range of binary correlations, because the underlying correlation matrix of the latent variables may not be positive definite. In this research, we proposed pair copula models, assuming the dependence between the binary variables is first order autoregressive (AR(1))or equicorrelated structure. Also, when Archimediean copula is used, most paper converted Kendall Tau to corresponding copula parameter, there is no explicit function of Pearson’s correlation coefficient …