Given the critical role of data availability for growth and innovation in financial services, especially small and mid-sized banks lack the data volumes required to fully leverage AI advancements for enhancing fraud detection, operational efficiency, and risk management. With existing solutions...

Given the critical role of data availability for growth and innovation in financial services, especially small and mid-sized banks lack the data volumes required to fully leverage AI advancements for enhancing fraud detection, operational efficiency, and risk management. With existing solutions...

The vision of a deep learning-empowered non-destructive evaluation technique aligns perfectly with the goal of zero-defect manufacturing, enabling manufacturers to detect and repair defects actively. However, the dearth of data in manufacturing is one of the biggest obstacles to realizing an...

Factors such as risk attitude, innovativeness, and financial literacy are crucial in agricultural and forest economics, especially amidst weather and market risks. Hence, understanding them is central for fostering a resilient primary sector. We surveyed 371 German farmers and 215 foresters in...

The emergence of Large Language Models (LLMs) has unlocked unprecedented potential for comprehending and generating human-like text, fueling advances in the finance domain - a tool that can shape investment strategies and market predictions. Nevertheless, challenges stemming from the necessity...

Synthetic microdata - data retaining the structure of original microdata while replacing original values with modeled values for the sake of privacy - presents an opportunity to increase access to useful microdata for data users while meeting the privacy and confidentiality requirements for data...

Models simulating household energy demand based on different occupant and household types and their behavioral patterns have received increasing attention over the last years due the need to better understand fundamental characteristics that shape the demand side. Most of the models described in...

Models simulating household energy demand based on different occupant and household types and their behavioral patterns have received increasing attention over the last years due the need to better understand fundamental characteristics that shape the demand side. Most of the models described in...

One major criticism against the use of synthetic data has been that the efforts necessary to generate useful synthetic data are so in- tense that many statistical agencies cannot afford them. We argue many lessons in this evolving field have been learned in the early years of synthetic data...

Distributions of business data are typically much more skewed than those for household or individual data and public knowledge of the underlying units is greater. As a results, national statistical offices (NSOs) rarely release establishment or firm-level business microdata due to the risk to...

This article describes how coffee rust has become a serious concern for many coffee farmers and manufacturers. The American Phytopathological Society discusses its importance saying this: “…the most economically important coffee disease in the world…” while “…in monetary value,...

The Census Bureau's Quarterly Workforce Indicators (QWI) provide detailed quarterly statistics on employment measures such as worker and job flows, tabulated by worker characteristics in various combinations. The data are released for several levels of NAICS industries and geography, the lowest...

A method, based on the Smirnov transform, for generating synthetic data with the statistical properties of Lévy-walks is presented. This method can be utilized for generating arbitrary prescribed probability density functions (pdf). A cybersecurity engineering problem associated with Internet...

A comparison between the probability similarities of a Distributed Denial-of-Service (DDoS) dataset and Lévy walks is presented. This effort validates Lévy walks as a model resembling DDoS probability features. In addition, a method, based on the Smirnov transform, for generating synthetic...

The partially linear single-index model is an interesting semiparametric model extended by the partially linear model and the single-index model, which supply a good balance between flexibility and parsimony. A robust estimation is proposed to fit the partially linear single-index model in case...

This thesis is comprised of three chapters. The first chapter (joint with John Haltiwanger, Julia Lane, and Kevin McKinney) explores a new way of capturing dynamics: following clusters of workers as they move across administrative entities. Information on firm dynamics is critical to...

Testing the accuracy of 3D modelling algorithms used for geological applications is extremely difficult as model results cannot be easily validated. This paper presents a new approach to evaluate the effectiveness of common interpolation algorithms used in 3D subsurface modelling, utilizing four...

The lack of data on how the social condition of Indigenous people varies throughout Australia has created difficulties in allocating government and community programs across Indigenous communities. In the past, spatial microsimulation has been used to derive small area estimates to overcome such...

Making published, scientific research data publicly available can benefit scientists and policy makers only if there is sufficient information for these data to be intelligible. Thus the necessary meta-data go beyond the scientific, technological detail and extend to the statistical approach and...

Presented at the Joint Statistical Meetings, Salt Lake City, UT.