Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Statistical Models (12)
- Applied Statistics (10)
- Statistical Methodology (8)
- Data Science (4)
- Social and Behavioral Sciences (4)
-
- Econometrics (3)
- Economics (3)
- Multivariate Analysis (3)
- Probability (3)
- Social Statistics (3)
- Agricultural and Resource Economics (2)
- Applied Mathematics (2)
- Behavioral Economics (2)
- Biostatistics (2)
- Categorical Data Analysis (2)
- Computer Sciences (2)
- Design of Experiments and Sample Surveys (2)
- Development Studies (2)
- Economic Theory (2)
- Engineering (2)
- Finance (2)
- Food Security (2)
- Growth and Development (2)
- Macroeconomics (2)
- Artificial Intelligence and Robotics (1)
- Aviation (1)
- Business (1)
- Institution
- Keyword
-
- Statistics (2)
- Tolerance interval (2)
- Asymmetry (1)
- Asymptotic relative efficiency (1)
- Ausubel's Theory of Meaningful Learning (1)
-
- Baseball (1)
- Batting Order (1)
- Bias (1)
- Bootstrapping (1)
- Calibration estimation (1)
- Causal Inference (1)
- College (1)
- Copulas (1)
- Crystal structure (1)
- Debiased Lasso (1)
- Demographics (1)
- Dependence (1)
- Distribution-free (1)
- Ebbinghaus's Spacing Effect Theory and Forgetting Curve (1)
- Electrochemical investigation (1)
- Exchange rates (1)
- Exponentially-modified Gaussian distribution (1)
- FBO (1)
- Flight Time to Proficiency (1)
- High Dimensional inference (1)
- High dimensional (1)
- Hydrogen evolution reaction (1)
- Isotonic regression (1)
- LightGBM (1)
- Linear Regression (1)
- Publication
- Publication Type
Articles 1 - 16 of 16
Full-Text Articles in Statistical Theory
Microplate-Like Metal Pyrophosphate Engineered On Ni-Foam Towards Multifunctional Electrode Material For Energy Conversion And Storage, Rishabh Srivastava
Microplate-Like Metal Pyrophosphate Engineered On Ni-Foam Towards Multifunctional Electrode Material For Energy Conversion And Storage, Rishabh Srivastava
Electronic Theses & Dissertations
High clean energy demand, dire need for sustainable development, and low carbon footprints are the few intuitive challenges, leading researchers to aim for research and development for high-performance energy devices. The development of materials used in energy devices is currently focused on enhancing the performance, electronic properties, and durability of devices. Tunning the attributes of transition metals using pyrophosphate (P2O7) ligand moieties can be a promising approach to meet the requirements of energy devices such as water electrolyzers and supercapacitors, although such a material’s configuration is rarely exposed for this purpose of study.
Herein, we grow …
Exploration And Statistical Modeling Of Profit, Caleb Gibson
Exploration And Statistical Modeling Of Profit, Caleb Gibson
Undergraduate Honors Theses
For any company involved in sales, maximization of profit is the driving force that guides all decision-making. Many factors can influence how profitable a company can be, including external factors like changes in inflation or consumer demand or internal factors like pricing and product cost. Understanding specific trends in one's own internal data, a company can readily identify problem areas or potential growth opportunities to help increase profitability.
In this discussion, we use an extensive data set to examine how a company might analyze their own data to identify potential changes the company might investigate to drive better performance. Based …
Generalized Ratio-Product Cum Regression Variance Estimator In Two-Phase Sampling, Isah Muhammad
Generalized Ratio-Product Cum Regression Variance Estimator In Two-Phase Sampling, Isah Muhammad
CBN Journal of Applied Statistics (JAS)
This study develops a flexible and efficient generalized ratio-product cum regression type estimator of population variance utilizing auxiliary variable in two-phase sampling that incorporates the properties of ratio-type and product-type estimators. The properties of the estimator were derived using first order approximation. The theoretical conditions under which the precision and the flexibility of the estimator is better than some classical estimators are also provided. Empirical evidence from five real datasets suggests that the proposed estimator outperforms the classical variance, ratio variance, product, and exponential ratio type estimators in terms of precision and efficiency. The estimator can be utilized to provide …
Modelling The Naira Exchange Rate Dependence Using Static And Time-Varying Copula, Kabir Katata
Modelling The Naira Exchange Rate Dependence Using Static And Time-Varying Copula, Kabir Katata
CBN Journal of Applied Statistics (JAS)
This paper examines the dependence structure of different currencies versus the Nigerian Naira using constant and time-varying copula. Daily Naira/USD, Naira/Yuan, Naira/Pound, and Naira/Euro exchange rates from 23 December 2011 to 12 May 2020 were utilised. We fitted eight constant and time-varying copula families using the exchange rate standardised residuals. The study finds that the Naira exchange rate may be estimated with student t-copula, Symmetrized Joe-Clayton (SJC), or Rotated Gumbel copula models and Autoregressive (AR)– Glosten Jagannathan RunkleGeneralized Autoregressive Conditional Heteroscedastic (GJR-GARCH) (1,1) models with skewed t residuals for margins. The Naira exchange rate returns is timevarying, tail-dependent, and asymmetric. …
The Private Pilot Check Ride: Applying The Spacing Effect Theory To Predict Time To Proficiency For The Practical Test, Michael Scott Harwin
The Private Pilot Check Ride: Applying The Spacing Effect Theory To Predict Time To Proficiency For The Practical Test, Michael Scott Harwin
Theses and Dissertations
This study examined the relationship between a set of targeted factors and the total flight time students needed to become ready to take the private pilot check ride. The study was grounded in Ebbinghaus’s (1885/1913/2013) forgetting curve theory and spacing effect, and Ausubel’s (1963) theory of meaningful learning. The research factors included (a) training time to proficiency, which represented the number of training days needed to become check-ride ready; (b) flight training program (Part 61 vs. Part 141); (c) organization offering the training program (2- or 4-year college/university vs. FBO); (d) scheduling policy (mandated vs. student-driven); and demographical variables, which …
Statistical Inference On Lung Cancer Screening Using The National Lung Screening Trial Data., Farhin Rahman
Statistical Inference On Lung Cancer Screening Using The National Lung Screening Trial Data., Farhin Rahman
Electronic Theses and Dissertations
This dissertation consists of three research projects on cancer screening probability modeling. In these projects, the three key modeling parameters (sensitivity, sojourn time, transition density) for cancer screening were estimated, along with the long-term outcomes (including overdiagnosis as one outcome), the optimal screening time/age, the lead time distribution, and the probability of overdiagnosis at the future screening time were simulated to provide a statistical perspective on the effectiveness of cancer screening programs. In the first part of this dissertation, a statistical inference was conducted for male and female smokers using the National Lung Screening Trial (NLST) chest X-ray data. A …
A Comparison Of Confidence Intervals In State Space Models, Jinyu Du
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 …
Improving The Efficiency Of Exponential Ratio-Type Estimator For Population Median: A Calibration Weight Adjustment Approach, Mathew J. Iseh, Kufre J. Bassey
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 …
Testing For Dice Control Based On Observations Of The Length Of The Shooter's Hand, Stewart N. Ethier, Hokwon Cho
Testing For Dice Control Based On Observations Of The Length Of The Shooter's Hand, Stewart N. Ethier, Hokwon Cho
International Conference on Gambling & Risk Taking
uploaded
Uconn Baseball Batting Order Optimization, Gavin Rublewski, Gavin Rublewski
Uconn Baseball Batting Order Optimization, Gavin Rublewski, Gavin Rublewski
Honors Scholar Theses
Challenging conventional wisdom is at the very core of baseball analytics. Using data and statistical analysis, the sets of rules by which coaches make decisions can be justified, or possibly refuted. One of those sets of rules relates to the construction of a batting order. Through data collection, data adjustment, the construction of a baseball simulator, and the use of a Monte Carlo Simulation, I have assessed thousands of possible batting orders to determine the roster-specific strategies that lead to optimal run production for the 2023 UConn baseball team. This paper details a repeatable process in which basic player statistics …
Two Sample Statistical Test For Location Parameters, Narinder Kumar, Arun Kumar
Two Sample Statistical Test For Location Parameters, Narinder Kumar, Arun Kumar
Journal of Modern Applied Statistical Methods
A class of distribution-free tests for the homogeneity of location parameters is proposed and compared with different competitors in terms of Pitman asymptotic relative efficiency. A numerical example is provided and a simulation study is made to check the performance of the tests.
National Residency Matching Program: Looking At The Data Through Linear Regressions, Jacklyn Tellez
National Residency Matching Program: Looking At The Data Through Linear Regressions, Jacklyn Tellez
Undergraduate Theses
The National Residency Matching Program (NRMP) oversees the process of medical school graduates being matched to a residency program. The NRMP determines both the hospital and residency program for medical students. Prior to matching, both hospital programs and students rank each other. The NRMP uses these lists to determine the matches. Four distinct models using data from hospitals and applicants were used to determine what characteristics lead to a chance of being matched. Each model went through multiple rounds of testing to determine the importance of the different independent variables. In each data set, the dependent variable is either the …
High-Dimensional Variable Selection Via Knockoffs Using Gradient Boosting, Amr Essam Mohamed
High-Dimensional Variable Selection Via Knockoffs Using Gradient Boosting, Amr Essam Mohamed
Dissertations
As data continue to grow rapidly in size and complexity, efficient and effective statistical methods are needed to detect the important variables/features. Variable selection is one of the most crucial problems in statistical applications. This problem arises when one wants to model the relationship between the response and the predictors. The goal is to reduce the number of variables to a minimal set of explanatory variables that are truly associated with the response of interest to improve the model accuracy. Effectively choosing the true influential variables and controlling the False Discovery Rate (FDR) without sacrificing power has been a challenge …
Tolerance Intervals For Various Regression Models, Xitong Zhou
Tolerance Intervals For Various Regression Models, Xitong Zhou
Theses and Dissertations--Statistics
Among statistical intervals, confidence intervals and prediction intervals are well-known and commonly used. In many applications, the problem becomes finding an interval that covers at least a certain proportion $P$ of the population for a characteristic of interest with a specified confidence level $(1-\alpha)$. And such interval is named a $P$-content, $(1-\alpha)$-confidence Tolerance Interval (TI). The topic of the dissertation is the utility of tolerance intervals for various regression models. We begin with a discussion of tolerance intervals for linear and nonlinear regression models. We then propose a bootstrap method of constructing TIs for Tobit regression to deal with censored …
High Dimensional Data Analysis: Variable Screening And Inference, Lei Fang
High Dimensional Data Analysis: Variable Screening And Inference, Lei Fang
Theses and Dissertations--Statistics
This dissertation focuses on the problem of high dimensional data analysis, which arises in many fields including genomics, finance, and social sciences. In such settings, the number of features or variables is much larger than the number of observations, posing significant challenges to traditional statistical methods.
To address these challenges, this dissertation proposes novel methods for variable screening and inference. The first part of the dissertation focuses on variable screening, which aims to identify a subset of important variables that are strongly associated with the response variable. Specifically, we propose a robust nonparametric screening method to effectively select the predictors …
Novel Modelling And Inference Considerations Involving The Exponentially-Modified Gaussian Distribution, Yanxi Li
Theses and Dissertations--Statistics
The exponentially-modified Gaussian (EMG) distribution is well-suited for analyzing data with positive skewness due to its characteristic positive skew from the exponential component. Despite its popularity in various fields, the EMG distribution has only been analyzed for univariate data without any regression settings. To address this limitation, we developed a generalized EMG regression model with covariates by assigning parametric functional forms to some or all of the parameters in the EMG distribution that vary with values of the covariates. To further perform data-clustering on observation points, we propose a competing regression model where the error structure is assumed to be …