应用统计
To optimize mobile health interventions and advance domain knowledge on intervention design, it is critical to understand how the intervention effect varies over time and with contextual information. This study aims to assess how a push…
Variation in a sample of molecular sequence data informs about the past evolutionary history of the sample's population. Traditionally, Bayesian modeling coupled with the standard coalescent, is used to infer the sample's bifurcating…
The role of cryptocurrencies within the financial systems has been expanding rapidly in recent years among investors and institutions. It is therefore crucial to investigate the phenomena and develop statistical methods able to capture…
Patients with traumatic brain injury (TBI) often experience pathological increases in intracranial pressure (ICP), leading to intracranial hypertension (tIH), a common and serious complication. Early warning of an impending rise in ICP…
Sector specific multifactor CES elasticity of substitution and the corresponding productivity growths are jointly measured by regressing the growths of factor-wise cost shares against the growths of factor prices. We use linked input-output…
In clinical trials, patients may discontinue treatments prematurely, breaking the initial randomization and, thus, challenging inference. Stakeholders in drug development are generally interested in going beyond the Intention-To-Treat (ITT)…
The recent COVID-19 pandemic has highlighted the need of studying extreme, life-threatening phenomena in advance. In this article, a zombie epidemic in Uusimaa region in Finland is modeled. A stochastic agent based simulation model is…
Psychometrics and quantitative psychology rely strongly on statistical models to measure psychological processes. As a branch of mathematics, geometry is inherently connected to measurement and focuses on properties such as distance and…
This manuscript proposes a novel methodology for developing an interpretable prediction model for irregular Electrocardiogram (ECG) classification, using features extracted by a 1-D Deconvolutional Neural Network (1-D DNN). Given the…
The age pension aims to assist eligible elderly Australians meet specific age and residency criteria in maintaining basic living standards. In designing efficient pension systems, government policymakers seek to satisfy the expectations of…
This paper employs a Bayesian methodology to predict the results of soccer matches in real-time. Using sequential data of various events throughout the match, we utilize a multinomial probit regression in a novel framework to estimate the…
Predicting the winner of an election is of importance to multiple stakeholders. To formulate the problem, we consider an independent sequence of categorical data with a finite number of possible outcomes in each. The data is assumed to be…
Motivated by the increasing abundance of data describing real-world networks that exhibit dynamical features, we propose an extension of the Exponential Random Graph Models (ERGMs) that accommodates the time variation of its parameters.…
The objective of this study is applying a utility based analysis to a comparatively efficient design experiment which can capture people's perception towards the various components of a commodity. Here we studied the multi-dimensional…
This study examines the effects of the F\'ed\'eration Internationale de l'Automobile (FIA) regulations on Formula 1 (F1) from 1990 to 2023, focusing on safety, racing dynamics, and spectacle. By analyzing data on fatalities, overtaking…
Monitoring networks increasingly aim to assimilate data from a large number of diverse sensors covering many sensing modalities. Bayesian optimal experimental design (OED) seeks to identify data, sensor configurations, or experiments which…
Given a collection of historical sports rankings, can one tell which player is the greatest of all time (i.e., the GOAT)? In this work, we design a data-driven random walk on the symmetric group to obtain a stationary distribution over…
This study develops a real-time framework for estimating the risk of near-misses by using high-fidelity two-dimensional (2D) risk indicator time-to-collision (TTC), which is calculated from high-resolution data collected by autonomous…
We consider the problem of predicting an individual's identity from accelerometry data collected during walking. In a previous paper we introduced an approach that transforms the accelerometry time series into an image by constructing its…
Risk-limiting audits (RLAs) can provide routine, affirmative evidence that reported election outcomes are correct by checking a random sample of cast ballots. An efficient RLA requires checking relatively few ballots. Here we construct…