Applied Statistics Commons^™

A Comparison Of Confidence Intervals In State Space Models, Jinyu Du

Statistical Science Theses and Dissertations

This thesis develops general procedures for constructing confidence intervals (CIs) of the error disturbance parameters (standard deviations) and transformations of the error disturbance parameters in time-invariant state space models (ssm). With only a set of observations, estimating individual error disturbance parameters accurately in the presence of other unknown parameters in ssm is a very challenging problem. We attempted to construct four different types of confidence intervals, Wald, likelihood ratio, score, and higher-order asymptotic intervals for both the simple local level model and the general time-invariant state space models (ssm). We show that for a simple local level model, both the …

Development And Testing Of A New Method For Velocity-Selecting White Dwarfs From Gaia By Galactic Population, Joseph Hammill

Doctoral Dissertations and Master's Theses

The detailed processes by which spiral galaxies form remains an open question in modern cosmology. Observations of the current configuration of spiral galaxies including the Milky Way reveal thin and thick disk and halo populations which must all be accounted for in formation theories and likely have distinct ages. Using the Milky Way as an example to probe this question, we are studying the formation history of these structures.

This work details our approach to age-dating the galaxy, velocity-selecting targets from a sample of white dwarfs from the Gaia DR3 catalog that have also been age-analysed using BASE-9. BASE-9 uses …

Quantifying Implicit Bias In Judicial Legal Opinions: A Natural Language Processing Approach, Philip N. Surendran

Quantitative Social Science Undergraduate Senior Theses

Implicit bias and criminal justice are two concepts that have long been intertwined. There is no justice without neutrality, and yet how do we tell if the actors enforcing the system are actually impartial? In this thesis, I utilize recent advancements in machine learning to attempt to answer this question. Specifically, I use natural language processing to examine the text of opinions written by judges in appellate courts, and I leverage these findings to build quantifiable measures of implicit bias. In particular, I look at the over/under-representation of certain emotions, sentiments and linguistic styles as a proxy for disparate treatment …

(R2025) Improving The Lda Linear Discriminant Analysis Method By Eliminating Redundant Variables For The Diagnosis Of Covid-19 Patients, Kianoush Fathi Vajargah, Hamid Mottaghi Golshan, Fazel Badakhshan Farahabadi

Applications and Applied Mathematics: An International Journal (AAM)

Nowadays, with the increase in data production speed, the process of data analysis has faced many problems because this big data is often accompanied by plug-in data and redundant data. Therefore, the use of dimensional methods in the pre-data analysis stage is necessary. In data mining, dimensional reduction is one of the most important steps in data pre-processing. Principal component analysis (PCA) and linear discriminant analysis (LDA) are often used to reduce dimensions in data mining. The LDA method is a monitored and controlled method but the PCA is not controlled method. When the number of samples in classes is …

On Colorings And Orientations Of Signed Graphs, Daniel Slilaty

Mathematics and Statistics Faculty Publications

A classical theorem independently due to Gallai and Roy states that a graph G has a proper k-coloring if and only if G has an orientation without coherent paths of length k. An analogue of this result for signed graphs is proved in this article.

(R2027) A New Class Of Pareto Distribution: Estimation And Its Applications, Anitta Susan Aniyan, Dais George

Applications and Applied Mathematics: An International Journal (AAM)

The classical Pareto distribution is a positively skewed and right heavy-tailed lifetime distribution having a lot many applications in various fields of science and social science. In this work, via logarithmic trans-formed method, a new three parameter lifetime distribution, an extension of classical Pareto distribution is generated. The different structural properties of the new distribution are studied. The model parameters are estimated by the method of maximum likelihood and Bayesian procedure. When all the three parameters of the distribution are unknown, the Bayes estimators cannot be obtained in a closed form and hence, the Lindley’s approximation under squared error loss …

Digital Economy, Institutional Quality And Economic Growth In Selected Countries, Olabode P. Olofin Mr.

CBN Journal of Applied Statistics (JAS)

This study examines the role of digital economy and institutional quality on economic growth of Bangladesh, Ethiopia, Kenya, and Nigeria. The study adopts the feasible generalized least square method with annual panel data from 1985 to 2017. Results show that digital economy, human capital and knowledge worker, and democratic accountability promote economic growth, while corruption, socioeconomic conditions, and bureaucratic quality retard economic growth. Furthermore, interaction of digital economy with corruption promotes growth. However, the interaction of digital economy with institutional quality retards economic growth, which could be due to the deteriorating institutional quality and low level of economic digitalization in …

Food Price And Inflation Adjustments In Nigeria: Evidence From Threshold Cointegration, Usman A. Bello, Aliyu R. Sanusi

CBN Journal of Applied Statistics (JAS)

This paper investigates two stages of transmission through which inflation stabilization policy affects headline inflation by estimating a threshold cointegration model. The paper finds that asymmetric monetary shocks passing-through food prices exerts inflationary pressure on consumer prices, and is characterized by deep asymmetric movement, large degree of stickiness in adjusting downward, while exhibiting upward momentum in correcting food price fall. In addition, asymmetries were found in consumer price adjustment as food price shock transmits substantial inflationary pressure to consumer prices, while disinflationary effect originating from a fall in food price is inconsequential. The coefficients of adjustment were found to be …

Dynamic Effect Of Exchange Rate Gap Shocks On Stock Market Deepening: Evidence From Nigeria, Kareem Abidemi Arikewuyo

CBN Journal of Applied Statistics (JAS)

The study examines the exchange rate gap shock–stock market deepening nexus in Nigeria using the structural VAR-X (SVAR-X) technique for the period 1986Q1 to 2018Q4. Findings reveal that exchange rate gap shock has a negative but statistically not significant effect on stock market deepening in Nigeria. It was also found that exchange rate passed–through interest rate from second to thirteen quarter, and further through financial openness whose effect, like exchange rate gap, was negative. This implies that exchange rate gap is significantly and negatively related to interest rate and financial openness in Nigeria. It is therefore recommended that the monetary …

Modelling The Impact Of Government Expenditure On Economic Growth In Nigeria: The Moderating Effects Of Oil And Non-Oil Revenue, Victor U. Ijirshar, Gaius M. Asombo, Florence D. Bundepuun, Ashifa Tersugh, Ayila Ngutsav

CBN Journal of Applied Statistics (JAS)

This study examines the relationship between government expenditure and economic growth and assesses the moderating effects of oil revenue and non-oil revenue in Nigeria from 1981 to 2021. The study uncovered short-term asymmetry in the government expenditure-economic growth nexus while the long-term relationship was symmetric. The study found that government expenditure is a significant determinant of economic growth in Nigeria and that oil and non-oil revenue influences the nexus between government expenditure and economic growth in Nigeria positively. The study recommends efficient management of oil revenue, directing investments during high revenue periods and ensuring fiscal sustainability. Government should also establish …

Improving The Efficiency Of Exponential Ratio-Type Estimator For Population Median: A Calibration Weight Adjustment Approach, Mathew J. Iseh, Kufre J. Bassey

CBN Journal of Applied Statistics (JAS)

This paper modifies the Bahl and Tuteja exponential ratio-type estimator for population median under simple random and stratified sampling schemes using calibration weight adjustment technique with supplementary information to vary the stratum weights. The bias and mean square error of the modified estimator were obtained up to the second-order approximation, which satisfies the necessary conditions for efficiency. The findings show that the new estimator surpasses existing estimators in efficiency gain. This suggests the appropriateness of calibration weight modification in boosting the efficiency of a population parameter estimator under stratified random sampling especially where the population parameter of the auxiliary variable …

Statistical And Biological Analyses Of Acoustic Signals In Estrildid Finches, Moises Rivera

Dissertations, Theses, and Capstone Projects

Acoustic communication is a process that involves auditory perception and signal processing. Discrimination and recognition further require cognitive processes and supporting mechanisms in order to successfully identify and appropriately respond to signal senders. Although acoustic communication is common across birds, classical research has largely disregarded the perceptual abilities of perinatal altricial taxa. Chapter 1 reviews the literature of perinatal acoustic stimulation in birds, highlighting the disproportionate focus on precocial birds (e.g., chickens, ducks, quails). The long-held belief that altricial birds were incapable of acoustic perception in ovo was only recently overturned, as researchers began to find behavioral and physiological evidence …

Data-Optimized Spatial Field Predictions For Robotic Adaptive Sampling: A Gaussian Process Approach, Zachary Nathan

Computer Science Senior Theses

We introduce a framework that combines Gaussian Process models, robotic sensor measurements, and sampling data to predict spatial fields. In this context, a spatial field refers to the distribution of a variable throughout a specific area, such as temperature or pH variations over the surface of a lake. Whereas existing methods tend to analyze only the particular field(s) of interest, our approach optimizes predictions through the effective use of all available data. We validated our framework on several datasets, showing that errors can decline by up to two-thirds through the inclusion of additional colocated measurements. In support of adaptive sampling, …

Statistical Methods To Generate Artificial Slot Floor Data For The Advancement Of Casino Related Research, Courtney Bonner, Anastasia (Stasi) D. Baran, Jason D. Fiege, Saman Muthukumarana

International Conference on Gambling & Risk Taking

Abstract:

A common difficulty when researching gambling topics is the availability of high-quality data sets for development and testing. Due to the high level of secrecy within the gambling industry, if data is obtained for research purposes it is often prohibitively obfuscated, incomplete, or aggregated. Although these data have allowed for advancement in academic work, it leaves both the researchers and readers left wondering about what would be possible if more detailed data sets were available. To mitigate the paucity of data available to researchers, we present a Markov chain-based statistical process for producing artificial event data for a simulated …

Interannual Variation Of Ichthyofaunal Utilization Of A Man-Made Salt Marsh Creek In Mission Bay, California, Maria Angst

Undergraduate Honors Theses

Marsh restoration and creation are increasingly being used to mitigate Southern California’s drastic decline in wetlands due to human activities. This study used minnow traps to resample the ichthyofauna of a created marsh (Crown Point Mitigation Site; CPMS) and an adjacent natural marsh (Kendall Frost) in Mission Bay, California, 26 years following the marsh creation. Data from this study were compared to data collected immediately after marsh creation from 1995-1998, and from 2021. Fishes captured included Fundulus parvipinnis, Gillichthys mirabilis, Acanthagobius flavimanus, Ctenogobius sagittula, and Mugil cephalus. Species richness and dominance measures were higher in the natural relative to the …

Stake Size And Wagering In A Professional Betting Environment – When Data Affects Decision Making, Anthony Bedford, Tristan Barnett

International Conference on Gambling & Risk Taking

In this work, we discuss the structure of a number of professional wagering organisations, and how they attempt to deal with the “Ender’s Game” effect – when knowledge of the true nature of the ‘war being wagered’ may have affected the process and choice of betting. We analyse the responses from professional wagering and betting organisations, whom operate predominately in Horseracing and sportsbetting, and they identify the importance of separation of decisions around choices to make and the stakes and size of wagers that are linked to the decisions. The proposed model, practically carried out by one company, is an …

Analytical Approach For Monitoring The Behavior Of Patients With Pancreatic Adenocarcinoma At Different Stages As A Function Of Time, Aditya Chakaborty Dr, Chris P. Tsokos Dr

Biology and Medicine Through Mathematics Conference

No abstract provided.

Optimizing Tumor Xenograft Experiments Using Bayesian Linear And Nonlinear Mixed Modelling And Reinforcement Learning, Mary Lena Bleile

Statistical Science Theses and Dissertations

Tumor xenograft experiments are a popular tool of cancer biology research. In a typical such experiment, one implants a set of animals with an aliquot of the human tumor of interest, applies various treatments of interest, and observes the subsequent response. Efficient analysis of the data from these experiments is therefore of utmost importance. This dissertation proposes three methods for optimizing cancer treatment and data analysis in the tumor xenograft context. The first of these is applicable to tumor xenograft experiments in general, and the second two seek to optimize the combination of radiotherapy with immunotherapy in the tumor xenograft …

An Application Of The Pagerank Algorithm To Ncaa Football Team Rankings, Morgan Majors

Honors Theses

We investigate the use of Google’s PageRank algorithm to rank sports teams. The PageRank algorithm is used in web searches to return a list of the websites that are of most interest to the user. The structure of the NCAA FBS football schedule is used to construct a network with a similar structure to the world wide web. Parallels are drawn between pages that are linked in the world wide web with the results of a contest between two sports teams. The teams under consideration here are the members of the 2021 Football Bowl Subdivision. We achieve a total ordering …

Movie Recommender System Using Matrix Factorization, Roland Fiagbe

Data Science and Data Mining

Recommendation systems are a popular and beneficial field that can help people make informed decisions automatically. This technique assists users in selecting relevant information from an overwhelming amount of available data. When it comes to movie recommendations, two common methods are collaborative filtering, which compares similarities between users, and content-based filtering, which takes a user’s specific preferences into account. However, our study focuses on the collaborative filtering approach, specifically matrix factorization. Various similarity metrics are used to identify user similarities for recommendation purposes. Our project aims to predict movie ratings for unwatched movies using the MovieLens rating dataset. We developed …