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Analyzing RNA-Seq Data in Complex Study Designs
Recently, RNA-seq experiments have become a routine technique in studying the transcriptomic regulations in various biomedical problems. The...
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Set-Based Tests for Genetic Association Studies with Interval-Censored Competing Risks Outcomes
Over the past decade, massive genetic compendiums such as the UK Biobank have gathered extensive genetic and phenotypic data that hold the potential...
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Estimation and backtesting of risk measures with emphasis on distortion risk measures
Statistical methodology has an important role to play in risk measurement. In this paper, we will review and discuss some statistical issues on risk...
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Predicting species-level vegetation cover using large satellite imagery data sets
Accurate information on the distribution of vegetation species is used as a proxy for the health of an ecosystem, a currency of international...
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A Distributed Regression Analysis Application Package Using
SAS Distributed regression is a privacy-preserving analytical method that performs multiple regression analysis using only summary-level information from...
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An Efficient Testing Procedure for High-Dimensional Mediators with FDR Control
The field of mediation analysis commonly explores the pathways that connect environmental exposures with health outcomes. With the development of...
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Functional Principal Component Analysis for Multiple Variables on Different Riemannian Manifolds
Functional principal component analysis (FPCA) is a very important dimension reduction tool for functional data analysis. The conventional FPCA...
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A Comparison of Estimation Methods for Shared Gamma Frailty Models
This paper compares six different estimation methods for shared frailty models via a series of simulation studies. A shared frailty model is a...
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Functional Causal Inference with Time-to-Event Data
Functional data analysis has proven to be a powerful tool for capturing and analyzing complex patterns and relationships in a variety of fields,...
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Scalable Bayesian p-generalized probit and logistic regression
The logit and probit link functions are arguably the two most common choices for binary regression models. Many studies have extended the choice of...
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Estimation in Multi-State Semi-Markov Models with a Cured Fraction and Masked Causes of Deaths
Analyses of disease-free survival data for certain cancer types indicate that cohorts of patients treated for cancer consist of individuals who are...
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Estimating Individualized Treatment Regimes to Optimize Incremental Cost-Effectiveness Ratio
Medical decision making can be challenging due to the trade-off between improving clinical efficacy and the associated medical costs. Evaluation of...
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Forecasting multidimensional autoregressive time series model with symmetric \(\alpha\)-stable noise using artificial neural networks
Artificial neural networks have been widely studied and applied in time series forecasting. However, the existing studies focus more on the...
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Analyzing Left-Truncated Samples with the Cox Model in the Presence of Missing Covariates
Delayed enrollment of subjects into a time-to-event study may result in a sample with biased outcome and covariate distributions. Additionally,...
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A Comparison of Bayesian Approximation Methods for Analyzing Large Spatial Skewed Data
Commonly, environmental processes are observed across different locations, and observations present skewed distributions. Recent proposals for...
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Hierarchical Bayesian Integrated Modeling of Age- and Sex-Structured Wildlife Population Dynamics
Biodiversity of large wild mammals is declining at alarming rates worldwide. It is therefore imperative to develop effective population conservation...
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Dynamic factor models for claim reserving
This study presents a new approach to claim reserving in the insurance industry using dynamic factor models (DFMs). Traditional methods often...
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Dirichlet compound negative multinomial mixture models and applications
In this paper, we consider an alternative parametrization of Dirichlet Compound Negative Multinomial (DCNM) using rising polynomials. The new...
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On the cost of risk misspecification in insurance pricing
In the non-life insurance industry, pricing is often done relative to individual criteria of policyholders. Various classification algorithms are in...
