Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Applied Statistics (30)
- Social and Behavioral Sciences (23)
- Statistical Methodology (11)
- Statistical Models (9)
- Probability (6)
-
- Biostatistics (5)
- Multivariate Analysis (5)
- Mathematics (4)
- Design of Experiments and Sample Surveys (3)
- Clinical Trials (2)
- Discrete Mathematics and Combinatorics (2)
- Other Statistics and Probability (2)
- Survival Analysis (2)
- Algebra (1)
- Biochemistry (1)
- Biochemistry, Biophysics, and Structural Biology (1)
- Bioinformatics (1)
- Biology (1)
- Biometry (1)
- Biotechnology (1)
- Cancer Biology (1)
- Categorical Data Analysis (1)
- Cell Biology (1)
- Cell and Developmental Biology (1)
- Computational Biology (1)
- Computer Sciences (1)
- Genetics (1)
- Institution
-
- Wayne State University (23)
- COBRA (3)
- East Tennessee State University (1)
- Georgia Southern University (1)
- Missouri State University (1)
-
- Old Dominion University (1)
- Portland State University (1)
- South Dakota State University (1)
- Southern Methodist University (1)
- The British University in Egypt (1)
- University of Kentucky (1)
- University of Montana (1)
- University of Nebraska - Lincoln (1)
- Virginia Commonwealth University (1)
- Western University (1)
- Keyword
-
- Bias (3)
- Censored data (2)
- Heteroscedasticity (2)
- High-dimensional inference (2)
- Mean square error (2)
-
- A/B testing (1)
- AUC (1)
- Acceptance sampling plan (1)
- Actual value and estimated value (1)
- Aging (1)
- Akaike and Bayesian information criterion (1)
- Analysis of outcomes (1)
- Ancillary variable (1)
- And T-K approximation. (1)
- Andersen LRT (1)
- Arcsine distribution (1)
- Asymmetry (1)
- Auxiliary information (1)
- Back-propagation (1)
- Bayesian analysis (1)
- Bayesian estimation (1)
- Behrens-Fisher problem (1)
- Berkson error (1)
- Binary data (1)
- Binomial model (1)
- Bootstrap (1)
- Bootstrap methods (1)
- Cancer genomics (1)
- Catalan numbers (1)
- Causal structure modeling (1)
- Publication
-
- Journal of Modern Applied Statistical Methods (23)
- UW Biostatistics Working Paper Series (2)
- Basic Science Engineering (1)
- COBRA Preprint Series (1)
- College of Graduate Studies: Theses & Dissertations (1)
-
- Community & Environmental Health Faculty Publications (1)
- Department of Statistics: Dissertations, Theses, and Student Research (1)
- Electronic Theses and Dissertations (1)
- Graduate Student Theses, Dissertations, & Professional Papers (1)
- Graduate Theses/Dissertations (1)
- Mathematics and Statistics Dissertations, Theses, and Final Project Papers (1)
- SDSU Data Science Symposium (1)
- Statistical Science Theses and Dissertations (1)
- Theses and Dissertations (1)
- Theses and Dissertations--Statistics (1)
- Western Research Forum (1)
- Publication Type
Articles 31 - 39 of 39
Full-Text Articles in Statistical Theory
Non Parametric Test For Testing Exponentiality Against Exponential Better Than Used In Laplace Transform Order, Mahmoud Mansour, M A W Mahmoud Prof.
Non Parametric Test For Testing Exponentiality Against Exponential Better Than Used In Laplace Transform Order, Mahmoud Mansour, M A W Mahmoud Prof.
Basic Science Engineering
In this paper, the test statistic for testing exponentiality against exponential better than used in Laplace transform order (EBUL) based on the Laplace transform technique is proposed. Pitman’s asymptotic efficiency of our test is calculated and compared with other tests. The percentiles of this test are tabulated. The powers of the test are estimated for famously used distributions in aging problems. In the case of censored data, our test is applied and the percentiles are also calculated and tabulated. Finally, real examples in different areas are utilized as practical applications for the proposed test.
Neural Shrubs: Using Neural Networks To Improve Decision Trees, Kyle Caudle, Randy Hoover, Aaron Alphonsus
Neural Shrubs: Using Neural Networks To Improve Decision Trees, Kyle Caudle, Randy Hoover, Aaron Alphonsus
SDSU Data Science Symposium
Decision trees are a method commonly used in machine learning to either predict a categorical response or a continuous response variable. Once the tree partitions the space, the response is either determined by the majority vote – classification trees, or by averaging the response values – regression trees. This research builds a standard regression tree and then instead of averaging the responses, we train a neural network to determine the response value. We have found that our approach typically increases the predicative capability of the decision tree. We have 2 demonstrations of this approach that we wish to present as …
Counting And Coloring Sudoku Graphs, Kyle Oddson
Counting And Coloring Sudoku Graphs, Kyle Oddson
Mathematics and Statistics Dissertations, Theses, and Final Project Papers
A sudoku puzzle is most commonly a 9 × 9 grid of 3 × 3 boxes wherein the puzzle player writes the numbers 1 - 9 with no repetition in any row, column, or box. We generalize the notion of the n2 × n2 sudoku grid for all n ∈ ℤ≥2 and codify the empty sudoku board as a graph. In the main section of this paper we prove that sudoku boards and sudoku graphs exist for all such n; we prove the equivalence of [3]'s construction using unions and products of graphs to the definition of …
Controlling For Confounding Via Propensity Score Methods Can Result In Biased Estimation Of The Conditional Auc: A Simulation Study, Hadiza I. Galadima, Donna K. Mcclish
Controlling For Confounding Via Propensity Score Methods Can Result In Biased Estimation Of The Conditional Auc: A Simulation Study, Hadiza I. Galadima, Donna K. Mcclish
Community & Environmental Health Faculty Publications
In the medical literature, there has been an increased interest in evaluating association between exposure and outcomes using nonrandomized observational studies. However, because assignments to exposure are not random in observational studies, comparisons of outcomes between exposed and nonexposed subjects must account for the effect of confounders. Propensity score methods have been widely used to control for confounding, when estimating exposure effect. Previous studies have shown that conditioning on the propensity score results in biased estimation of conditional odds ratio and hazard ratio. However, research is lacking on the performance of propensity score methods for covariate adjustment when estimating the …
Some New Generalized Distribution Via Lindley-Weibuli And Lindley-Log-Logistic Distributions With Applications, Soliu A. Raheem
Some New Generalized Distribution Via Lindley-Weibuli And Lindley-Log-Logistic Distributions With Applications, Soliu A. Raheem
College of Graduate Studies: Theses & Dissertations
In this thesis, new generalized distributions, namely Beta Lindley-Log-Logistic (BLLLoG) distribution, Marshall-Olkin Lindley-Weibull (MOLW) distribution, and Gamma LindleyWeibull (GLW) distribution as well as related sub-distributions are proposed. Series expansion of the densities are obtained. Statistical properties of these distributions, including hazard function, reverse hazard function, moments, reliability, quantile function, mean deviations, Bonferroni and Lorenz curves, entropy and Fisher information are derived. Method of maximum likelihood is used to estimate the parameters of the new distributions. Monte Carlo simulation is employed to examine the performance of the proposed distributions. Applications of the generalized distributions to real lifetime data are presented to …
Modeling Stochastically Intransitive Relationships In Paired Comparison Data, Ryan Patrick Alexander Mcshane
Modeling Stochastically Intransitive Relationships In Paired Comparison Data, Ryan Patrick Alexander Mcshane
Statistical Science Theses and Dissertations
If the Warriors beat the Rockets and the Rockets beat the Spurs, does that mean that the Warriors are better than the Spurs? Sophisticated fans would argue that the Warriors are better by the transitive property, but could Spurs fans make a legitimate argument that their team is better despite this chain of evidence?
We first explore the nature of intransitive (rock-scissors-paper) relationships with a graph theoretic approach to the method of paired comparisons framework popularized by Kendall and Smith (1940). Then, we focus on the setting where all pairs of items, teams, players, or objects have been compared to …
A Flexible Zero-Inflated Poisson Regression Model, Eric S. Roemmele
A Flexible Zero-Inflated Poisson Regression Model, Eric S. Roemmele
Theses and Dissertations--Statistics
A practical problem often encountered with observed count data is the presence of excess zeros. Zero-inflation in count data can easily be handled by zero-inflated models, which is a two-component mixture of a point mass at zero and a discrete distribution for the count data. In the presence of predictors, zero-inflated Poisson (ZIP) regression models are, perhaps, the most commonly used. However, the fully parametric ZIP regression model could sometimes be restrictive, especially with respect to the mixing proportions. Taking inspiration from some of the recent literature on semiparametric mixtures of regressions models for flexible mixture modeling, we propose a …
Statistical Designs For Network A/B Testing, Victoria V. Pokhilko
Statistical Designs For Network A/B Testing, Victoria V. Pokhilko
Theses and Dissertations
A/B testing refers to the statistical procedure of experimental design and analysis to compare two treatments, A and B, applied to different testing subjects. It is widely used by technology companies such as Facebook, LinkedIn, and Netflix, to compare different algorithms, web-designs, and other online products and services. The subjects participating in these online A/B testing experiments are users who are connected in different scales of social networks. Two connected subjects are similar in terms of their social behaviors, education and financial background, and other demographic aspects. Hence, it is only natural to assume that their reactions to online products …
Statistical Modeling Of Influenza-Like-Illness In Montana Using Spatial And Temporal Methods, Benjamin A. Stark
Statistical Modeling Of Influenza-Like-Illness In Montana Using Spatial And Temporal Methods, Benjamin A. Stark
Graduate Student Theses, Dissertations, & Professional Papers
Studying air pollution and public health has been a historically important question in science. It has long been hypothesized that severe air pollution conditions lead to negative implications in basic human health. Primarily, areas thats are prone to severe degrees of human pollution are the focus of such studies. Such research relating to less populated areas are scarce, and this scarcity raises the question of how such pollution dynamics (human-made and natural) influence human health in more rural areas.
The aim of this study is to explore this hole in research; in particular we explore possible links between air pollution …