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Articles 1 - 13 of 13
Full-Text Articles in Statistical Methodology
Testing For Dice Control At Craps, Stewart N. Ethier
Testing For Dice Control At Craps, Stewart N. Ethier
UNLV Gaming Research & Review Journal
Dice control involves “setting” the dice and then throwing them carefully, in the hope of influencing the outcomes and gaining an advantage at craps. How does one test for this ability? To specify the alternative hypothesis, we need a statistical model of dice control. Two have been suggested in the gambling literature, namely the Smith–Scott model and the Wong–Shackleford model. Both models are parameterized by θ ∈ [0, 1], which measures the shooter’s level of control. We propose and compare four test statistics: (a) the sample proportion of 7s; (b) the sample proportion of pass-line wins; (c) the sample mean …
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
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 …
Addressing The Ecological Fallacy With Lagrangian Inference, Michael Schwob
Addressing The Ecological Fallacy With Lagrangian Inference, Michael Schwob
Calvert Undergraduate Research Awards
Most epidemiologists elect to use statistical models that use population-level data to make inference on the spread of some virus or disease. This has become commonplace in the fields of epidemiology and biostatistics since most data used to construct and verify epidemic models are recorded at the population-level. Obtaining inference from a population-level model may be beneficial in studying the spread of disease in a homogeneous population, but the use of such models to describe a heterogeneous population results in inadequate inference. The inaccuracy of these models is further amplified when one tries to make individual-level inference from these population-level …
Quest For Continuous Improvement: Gathering Feedback And Data Through Multiple Methods To Evaluate And Improve A Library’S Discovery Tool, Jeanne M. Brown
Quest For Continuous Improvement: Gathering Feedback And Data Through Multiple Methods To Evaluate And Improve A Library’S Discovery Tool, Jeanne M. Brown
Library Faculty Presentations
Summon at UNLV
- Implemented fall 2011: a web-scale discovery tool
- Expectations for Summon
- Continuous Summon Improvement (CSI)Group
The environment
- User changes
- Library changes
- Vendor changes
- Product changes
- Complex information environment
- Change + complexity = need to assess using multiple streams of feedback
Automating Construction And Selection Of A Neural Network Using Stochastic Optimization, Jason Lee Hurt
Automating Construction And Selection Of A Neural Network Using Stochastic Optimization, Jason Lee Hurt
UNLV Theses, Dissertations, Professional Papers, and Capstones
An artificial neural network can be used to solve various statistical problems by approximating a function that provides a mapping from input to output data. No universal method exists for architecting an optimal neural network. Training one with a low error rate is often a manual process requiring the programmer to have specialized knowledge of the domain for the problem at hand.
A distributed architecture is proposed and implemented for generating a neural network capable of solving a particular problem without specialized knowledge of the problem domain. The only knowledge the application needs is a training set that the network …
Management And Support Of Shared Integrated Library Systems, Jason Vaughan, Kristen Costello
Management And Support Of Shared Integrated Library Systems, Jason Vaughan, Kristen Costello
Library Faculty Research
The University of Nevada, Las Vegas (UNLV) University Libraries has hosted and managed a shared integrated library system (ILS) since 1989. The system and the number of partner libraries sharing the system has grown significantly over the past two decades. Spurred by the level of involvement and support contributed by the host institution, the authors administered a comprehensive survey to current Innovative Interfaces libraries. Research findings are combined with a description of UNLV’s local practices to provide substantial insights into shared funding, support, and management activities associated with shared systems.
Analysis Of Morris Water Maze Data With Bayesian Statistical Methods, Maxym V. Myroshnychenko, Anton Westveld, Jefferson Kinney
Analysis Of Morris Water Maze Data With Bayesian Statistical Methods, Maxym V. Myroshnychenko, Anton Westveld, Jefferson Kinney
Festival of Communities: UG Symposium (Posters)
Neuroscientists commonly use a Morris Water Maze to assess learning in rodents. In his kind of a maze, the subjects learn to swim toward a platform hidden in opaque water as they orient themselves according to the cues on the walls. This protocol presents a challenge to statistical analysis, because an artificial cut-off must be set for those experimental subjects that do not reach the platform so as they do not drown from exhaustion. This fact leads to the data being right censored. In our experimental data, which compares learning in rodents that have chemically induced symptoms of schizophrenia to …
Statistical Inferences For Functions Of Parameters Of Several Pareto And Exponential Populations With Application In Data Traffic, Sumith Gunasekera
Statistical Inferences For Functions Of Parameters Of Several Pareto And Exponential Populations With Application In Data Traffic, Sumith Gunasekera
UNLV Theses, Dissertations, Professional Papers, and Capstones
In this dissertation, we discuss the usability and applicability of three statistical inferential frameworks--namely, the Classical Method, which is sometimes referred to as the Conventional or the Frequentist Method, based on the approximate large sample approach, the Generalized Variable Method based on the exact generalized p -value approach, and the Bayesian Method based on prior densities--for solving existing problems in the area of parametric estimation. These inference procedures are discussed through Pareto and exponential distributions that are widely used to model positive random variables relevant to social, scientific, actuarial, insurance, finance, investments, banking, and many other types of observable phenomena. …
Monaco/Mavric Evaluation For Facility Shielding And Dose Rate Analysis, Charlotta Sanders, Denis Beller
Monaco/Mavric Evaluation For Facility Shielding And Dose Rate Analysis, Charlotta Sanders, Denis Beller
Reactor Campaign (TRP)
The dimensions and the large amount of shielding required for Global Nuclear Energy Partnership (GNEP) facilities, advanced radiation shielding, and dose computation techniques are beyond today’s capabilities and will certainly be required. With the Generation IV Nuclear Energy System Initiative, it will become increasingly important to be able to accurately model advanced Boiling Water Reactor and Pressurized Water Reactor facilities, and to calculate dose rates at all locations within a containment (e.g., resulting from radiations from the reactor as well as the from the primary coolant loop) and adjoining structures (e.g., from the spent fuel pool).
The MAVRIC sequence is …
Implementation Of Uncertainty Propagation In Triton/Keno, Charlotta Sanders, Denis Beller
Implementation Of Uncertainty Propagation In Triton/Keno, Charlotta Sanders, Denis Beller
Reactor Campaign (TRP)
Monte Carlo methods are beginning to be used for three dimensional fuel depletion analyses to compute various quantities of interest, including isotopic compositions of used nuclear fuel. The TRITON control module, available in the SCALE 5.1 code system, can perform three-dimensional (3-D) depletion calculations using either the KENO V.a or KENO-VI Monte Carlo transport codes, as well as the two-dimensional (2-D) NEWT discrete ordinates code. To overcome problems such as spatially nonuniform neutron flux and non-uniform statistical uncertainties in computed reaction rates and to improve the fidelity of calculations using Monte Carlo methods, uncertainty propagation is needed for depletion calculations.
Implementation Of Uncertainty Propagation In Triton/Keno: To Support The Global Nuclear Energy Partnership, Charlotta Sanders, Denis Beller
Implementation Of Uncertainty Propagation In Triton/Keno: To Support The Global Nuclear Energy Partnership, Charlotta Sanders, Denis Beller
Reactor Campaign (TRP)
Monte Carlo methods are beginning to be used for three-dimensional fuel depletion analyses to compute various quantities of interest, including isotopic compositions of used fuel.1 The TRITON control module, available in the SCALE 5.1 code system, can perform three dimensional (3-D) depletion calculations using either the KENO V.a or KENO-VI Monte Carlo transport codes, as well as the two-dimensional (2- D) NEWT discrete ordinates code. For typical reactor systems, the neutron flux is not spatially uniform. For Monte Carlo simulations, this results in non-uniform statistical uncertainties in the computed reaction rates. For spatial regions where the flux is low, e.g., …
Monaco/Mavric Evaluation For Facility Shielding And Dose Rate Analysis: To Support The Global Nuclear Energy Partnership, Charlotta Sanders, Denis Beller
Monaco/Mavric Evaluation For Facility Shielding And Dose Rate Analysis: To Support The Global Nuclear Energy Partnership, Charlotta Sanders, Denis Beller
Reactor Campaign (TRP)
Monte Carlo methods are used to compute fluxes or dose rates over large areas using mesh tallies. For problems that demand that the uncertainty in each mesh cell be less than some set maximum, computation time is controlled by the cell with the largest uncertainty. This issue becomes quite troublesome in deep-penetration problems, and advanced variance reduction techniques are required to obtain reasonable uncertainties over large areas.
In this project the MAVRIC sequence will be evaluated along with the Monte Carlo engine Monaco to investigate its effectiveness and usefulness in facility shielding and dose rate analyses. A previously MCNP-evaluated cask …
Ramping Up Assessment At The Unlv Libraries, Jeanne M. Brown
Ramping Up Assessment At The Unlv Libraries, Jeanne M. Brown
Library Faculty Research
Purpose – Sets out to describe the development of an assessment program at UNLV Libraries and current assessment activities.
Design/methodology/approach – Assessment activities are first placed in organizational context, distinguishing between assessment initiated by departments, and assessment done library-wide. Common expressions of resistance to assessment are noted, followed by the library and campus context relating to assessment. The impact of technology and of the LibQual+ survey is discussed.
Findings – Assessment activities at UNLV Libraries have strengthened and diversified over the last several years, thanks to several factors including the guidance of its dean, the development of technology and human …