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Articles 1951 - 1980 of 2920

Full-Text Articles in Statistics and Probability

Bayesian Analysis For Component Manufacturing Processes, L. V. Nandakishore Nov 2010

Bayesian Analysis For Component Manufacturing Processes, L. V. Nandakishore

Journal of Modern Applied Statistical Methods

In manufacturing processes various machines are used to produce the same product. Based on the age, make, etc., of the machines the output may not always follow the same distribution. An attempt is made to introduce Bayesian techniques for a two machine problem. Two cases are presented in this article.

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Neighbor Balanced Block Designs For Two Factors, Seema Jaggi, Cini Varghese, N. R. Abeynayake Nov 2010

Neighbor Balanced Block Designs For Two Factors, Seema Jaggi, Cini Varghese, N. R. Abeynayake

Journal of Modern Applied Statistical Methods

The concept of Neighbor Balanced Block (NBB) designs is defined for the experimental situation where the treatments are combinations of levels of two factors and only one of the factors exhibits a neighbor effect. Methods of constructing complete NBB designs for two factors in a plot that is strongly neighbor balanced for one factor are obtained. These designs are variance balanced for estimating the direct effects of contrasts pertaining to combinations of levels of both the factors. An incomplete NBB design for two factors is also presented and is found to be partially variance balanced with three associate classes.

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Ann Forecasting Models For Ise National-100 Index, Ozer Ozdemir, Atilla Aslanargun, Senay Asma Nov 2010

Ann Forecasting Models For Ise National-100 Index, Ozer Ozdemir, Atilla Aslanargun, Senay Asma

Journal of Modern Applied Statistical Methods

Prediction of the outputs of real world systems with accuracy and high speed is crucial in financial analysis due to its effects on worldwide economics. Because the inputs of the financial systems are timevarying functions, the development of algorithms and methods for modeling such systems cannot be neglected. The most appropriate forecasting model for the ISE national-100 index was investigated. Box- Jenkins autoregressive integrated moving average (ARIMA) and artificial neural networks (ANN) are considered by using several evaluations. Results showed that the ANN model with linear architecture better fits the candidate data.

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Markov Chain Analysis And Student Academic Progress: An Empirical Comparative Study, Shafiqah Alawadhi, Mokhtar Konsowa Nov 2010

Markov Chain Analysis And Student Academic Progress: An Empirical Comparative Study, Shafiqah Alawadhi, Mokhtar Konsowa

Journal of Modern Applied Statistical Methods

An application of Markov Chain Analysis of student flow at Kuwait University is presented based on a random sample of 1,100 students from the academic years 1996-1997 to 2004-2005. Results were obtained for each college and in total which allows for a comparative study. The students’ mean lifetimes in different levels of study in the colleges as well as the percentage of dropping out of the system are estimated.

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Reducing Selection Bias In Analyzing Longitudinal Health Data With High Mortality Rates, Xian Liu, Charles C. Engel, Han Kang, Kristie L. Gore Nov 2010

Reducing Selection Bias In Analyzing Longitudinal Health Data With High Mortality Rates, Xian Liu, Charles C. Engel, Han Kang, Kristie L. Gore

Journal of Modern Applied Statistical Methods

Two longitudinal regression models, one parametric and one nonparametric, are developed to reduce selection bias when analyzing longitudinal health data with high mortality rates. The parametric mixed model is a two-step linear regression approach, whereas the nonparametric mixed-effects regression model uses a retransformation method to handle random errors across time.

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The Positive Solutions Of The Matukuma Equation And The Problem Of Finite Radius And Finite Mass, Jurgen Batt, Yi Li Nov 2010

The Positive Solutions Of The Matukuma Equation And The Problem Of Finite Radius And Finite Mass, Jurgen Batt, Yi Li

Mathematics and Statistics Faculty Publications

This work is an extensive study of the 3 different types of positive solutions of the Matukuma equation 1r2(r2ϕ′)′=−rλ−2(1+r2)λ/2ϕp,p>1,λ>0 : the E-solutions (regular at r = 0), the M-solutions (singular at r = 0) and the F-solutions (whose existence begins away from r = 0). An essential tool is a transformation of the equation into a 2-dimensional asymptotically autonomous system, whose limit sets (by a theorem of H. R. Thieme) are the limit sets of Emden–Fowler systems, and serve as a characterization of the different solutions. The emphasis lies on the study of the M …

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The Not-So-Quiet Revolution: Cautionary Comments On The Rejection Of Hypothesis Testing In Favor Of A “Causal” Modeling Alternative, Daniel H. Robinson, Joel R. Levin Nov 2010

The Not-So-Quiet Revolution: Cautionary Comments On The Rejection Of Hypothesis Testing In Favor Of A “Causal” Modeling Alternative, Daniel H. Robinson, Joel R. Levin

Journal of Modern Applied Statistical Methods

Rodgers (2010) recently applauded a revolution involving the increased use of statistical modeling techniques. It is argued that such use may have a downside, citing empirical evidence in educational psychology that modeling techniques are often applied in cross-sectional, correlational studies to produce unjustified causal conclusions and prescriptive statements.

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Notes On Hypothesis Testing Under A Single-Stage Design In Phase Ii Trial, Kung-Jong Lui Nov 2010

Notes On Hypothesis Testing Under A Single-Stage Design In Phase Ii Trial, Kung-Jong Lui

Journal of Modern Applied Statistical Methods

A primary objective of a phase II trial is to determine future development is warranted for a new treatment based on whether it has sufficient activity against a specified type of tumor. Limitations exist in the commonly-used hypothesis setting and the standard test procedure for a phase II trial. This study reformats the hypothesis setting to mirror the clinical decision process in practice. Under the proposed hypothesis setting, the critical points and the minimum required sample size for a desired power of finding a superior treatment at a given α -level are presented. An example is provided to illustrate how …

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Adjusted Confidence Interval For The Population Median Of The Exponential Distribution, Moustafa Omar Ahmed Abu-Shawiesh Nov 2010

Adjusted Confidence Interval For The Population Median Of The Exponential Distribution, Moustafa Omar Ahmed Abu-Shawiesh

Journal of Modern Applied Statistical Methods

The median confidence interval is useful for one parameter families, such as the exponential distribution, and it may not need to be adjusted if censored observations are present. In this article, two estimators for the median of the exponential distribution, MD, are considered and compared based on the sample median and the maximum likelihood method. The first estimator is the sample median, MD1, and the second estimator is the maximum likelihood estimator of the median, MDMLE. Both estimators are used to propose a modified confidence interval for the population median of the exponential distribution, MD …

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A Comparison Between Unbiased Ridge And Least Squares Regression Methods Using Simulation Technique, Mowafaq M. Al-Kassab, Omar Q. Qwaider Nov 2010

A Comparison Between Unbiased Ridge And Least Squares Regression Methods Using Simulation Technique, Mowafaq M. Al-Kassab, Omar Q. Qwaider

Journal of Modern Applied Statistical Methods

The parameters of the multiple linear regression are estimated using least squares ( B̂LS ) and unbiased ridge regression methods (B̂(KI,J)). Data was created for fourteen independent variables with four different values of correlation between these variables using Monte Carlo techniques. The above methods were compared using the mean squares error criterion. Results show that the unbiased ridge method is preferable to the least squares method.

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A General Class Of Chain-Type Estimators In The Presence Of Non-Response Under Double Sampling Scheme, Sunil Kumar, Housila P. Singh, Sandeep Bhougal Nov 2010

A General Class Of Chain-Type Estimators In The Presence Of Non-Response Under Double Sampling Scheme, Sunil Kumar, Housila P. Singh, Sandeep Bhougal

Journal of Modern Applied Statistical Methods

General class chain ratio type estimators for estimating the population mean of a study variable are examined in the presence of non-response under a double sampling scheme using a factor-type estimator (FTE). Properties of the suggested estimators are studied and compared to those of existing estimators. An empirical study is carried out to demonstrate the performance of the suggested estimators; empirical results support the theoretical study.

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On Scientific Research: The Role Of Statistical Modeling And Hypothesis Testing, Lisa L. Harlow Nov 2010

On Scientific Research: The Role Of Statistical Modeling And Hypothesis Testing, Lisa L. Harlow

Journal of Modern Applied Statistical Methods

Comments on Rodgers (2010a, 2010b) and Robinson and Levin (2010) are presented. Rodgers (2010a) initially reported on a growing trend towards more mathematical and statistical modeling; and a move away from null hypothesis significance testing (NHST). He defended and clarified those views in his sequel. Robinson and Levin argued against the perspective espoused by Rodgers and called for more research using experimentally manipulated interventions and less emphasis on correlational research and ill-founded prescriptive statements. In this response, the goal of science and major scientific approaches are discussed as well as their strengths and shortcomings. Consideration is given to how their …

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Nonlinear Trigonometric Transformation Time Series Modeling, K. A. Bashiru, O. E. Olowofeso, S. A. Owabumoye Nov 2010

Nonlinear Trigonometric Transformation Time Series Modeling, K. A. Bashiru, O. E. Olowofeso, S. A. Owabumoye

Journal of Modern Applied Statistical Methods

The nonlinear trigonometric transformation and augmented nonlinear trigonometric transformation with a polynomial of order two was examined. The two models were tested and compared using daily mean temperatures for 6 major towns in Nigeria with different rates of missing values. The results were used to determine the consistency and efficiency of the models formulated.

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Application Of The Fractional Diffusion Equation For Predicting Market Behaviour, Jonathan Blackledge Oct 2010

Application Of The Fractional Diffusion Equation For Predicting Market Behaviour, Jonathan Blackledge

Articles

Most Financial modelling system rely on an underlying hypothesis known as the Eficient Market Hypothesi (EMH) including the famous BlackScholes formula for placing an option. However, the EMH has a fundamental flaw: it is based on the assumption that economic processes are normally distributed and it has long been known that this is not the case. This fundamental assumption leads to a number of shortcomings associated with using the EMH to analyse financial data which includes failure to predict the future volatility of a market share value. This paper introduces a new financial risk assessment model based on Levy statistics …

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Statistical Image Recovery From Laser Speckle Patterns With Polarization Diversity, Donald B. Dixon Sep 2010

Statistical Image Recovery From Laser Speckle Patterns With Polarization Diversity, Donald B. Dixon

Theses and Dissertations

This research extends the theory and understanding of the laser speckle imaging technique. This non-traditional imaging technique may be employed to improve space situational awareness and image deep space objects from a ground-based sensor system. The use of this technique is motivated by the ability to overcome aperture size limitations and the distortion effects from Earth’s atmosphere. Laser speckle imaging is a lensless, coherent method for forming two-dimensional images from their autocorrelation functions. Phase retrieval from autocorrelation data is an ill-posed problem where multiple solutions exist. This research introduces polarization diversity as a method for obtaining additional information so the …

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Early Stopping Of A Neural Network Via The Receiver Operating Curve., Daoping Yu Aug 2010

Early Stopping Of A Neural Network Via The Receiver Operating Curve., Daoping Yu

Electronic Theses and Dissertations

This thesis presents the area under the ROC (Receiver Operating Characteristics) curve, or abbreviated AUC, as an alternate measure for evaluating the predictive performance of ANNs (Artificial Neural Networks) classifiers. Conventionally, neural networks are trained to have total error converge to zero which may give rise to over-fitting problems. To ensure that they do not over fit the training data and then fail to generalize well in new data, it appears effective to stop training as early as possible once getting AUC sufficiently large via integrating ROC/AUC analysis into the training process. In order to reduce learning costs involving the …

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Arima Model For Forecasting Poisson Data: Application To Long-Term Earthquake Predictions, Wangdong Fu Aug 2010

Arima Model For Forecasting Poisson Data: Application To Long-Term Earthquake Predictions, Wangdong Fu

UNLV Theses, Dissertations, Professional Papers, and Capstones

Earthquakes that occurred worldwide during the period of 1896 to 2009 with magnitude greater than or equal to 8.0 on the Richter scale are assumed to follow a Poisson process. Autoregressive Integrated Moving Average models are presented to fit the empirical recurrence rates, and to predict future large earthquakes. We show valuable modeling and computational techniques for the point processes and time series data. Specifically, for the proposed methodology, we address the following areas: data management and graphic presentation, model fitting and selection, model validation, model and data sensitivity analysis, and forecasting.

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The Generation Of Domestic Electricity Load Profiles Through Markov Chain Modelling, Aidan Duffy, Fintan Mcloughlin, Michael Conlon Jul 2010

The Generation Of Domestic Electricity Load Profiles Through Markov Chain Modelling, Aidan Duffy, Fintan Mcloughlin, Michael Conlon

Conference Papers

Micro-generation technologies such as photovoltaics and micro-wind power are becoming increasing popular among homeowners, mainly a result of policy support mechanisms helping to improve cost competiveness as compared to traditional fossil fuel generation. National government strategies to reduce electricity demand generated from fossil fuels and to meet European Union 20/20 targets is driving this change. However, the real performance of these technologies in a domestic setting is not often known as high time resolution models for domestic electricity load profiles are not readily available. As a result, projections in terms of reducing electricity demand and financial paybacks for these micro-generation …

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Statistical Analysis Of Texas Holdem Poker, Daniel Bragonier Jun 2010

Statistical Analysis Of Texas Holdem Poker, Daniel Bragonier

Statistics

Gathered lifetime online Poker data for Mike Linn. Attempted to analyze data to obtain information to maximize profit. Techniques included Univariate Analysis, Regression analysis, Anova analysis, Logistic Regression, and outlier Analysis. After the analysis, nothing of supreme importance or sustenance was found. Encountered issues with too much power. Results lead to plenty of statistical significance, but little practical significance. Results showed that the data did not provide all the answers that were being sought after, but there was some value in examining the data in a strict statistical manner.

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Derivation Of Mass Independent Quantum Treatment Of Phenomenon, David Parker May 2010

Derivation Of Mass Independent Quantum Treatment Of Phenomenon, David Parker

Journal of Modern Applied Statistical Methods

The derivation and applications is presented of a spatial variable or spatial radius which is related to the inertia or mass-energy of any quantum body by a Lorentz invariant relation. Mass independent DeBroglie and Schroedinger equations are derived and applied to the resolution of the linguistic incompatibility between quantum theory and the geometrical weak equivalence principle. The equivalence principle is restated in terms of the spatial radius. The gravitational attraction between bodies and the relativistic energy are both presented in terms of the spatial radius follows. The ratio of the gravitational force to the Coulomb force at the Planck scale …

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Ranked Set Sampling Using Auxiliary Variables Of A Randomized Response Procedure For Estimating The Mean Of A Sensitive Quantitative Character, Carlos N. Bouza May 2010

Ranked Set Sampling Using Auxiliary Variables Of A Randomized Response Procedure For Estimating The Mean Of A Sensitive Quantitative Character, Carlos N. Bouza

Journal of Modern Applied Statistical Methods

The analysis of the behavior of estimators of the mean of a sensitive variable is considered when a randomized response procedure is used. The results deal with the inference based on simple random sampling with replacement study design. A study of the behavior of the procedures for a ranked set sampling design is developed. A gain in accuracy is generally associated with the proposed alternative model.

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An Equivalence Test Based On N And P, Markus Neuhäeuser May 2010

An Equivalence Test Based On N And P, Markus Neuhäeuser

Journal of Modern Applied Statistical Methods

An equivalence test is proposed which is based on the P-value of a test for a difference and the sample size. This test may be especially appropriate for an exploratory re-analysis if only a non-significant test for a difference was reported. Thus, neither a confidence interval is available, nor is there access to the raw data. The test is illustrated using two examples; for both applications the smallest equivalence range for which equivalence could be demonstrated is calculated.

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The Effectiveness Of Stepwise Discriminant Analysis As A Post Hoc Procedure To A Significant Manova, Erik L. Heiny, Daniel J. Mundform May 2010

The Effectiveness Of Stepwise Discriminant Analysis As A Post Hoc Procedure To A Significant Manova, Erik L. Heiny, Daniel J. Mundform

Journal of Modern Applied Statistical Methods

The effectiveness of SWDA as a post hoc procedure in a two-way MANOVA was examined using various numbers of dependent variables, sample sizes, effect sizes, correlation structures, and significance levels. The procedure did not work well in general except with small numbers of variables, larger samples and low correlations between variables.

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Model Based Vs. Model Independent Tests For Cross-Correlation, H.E.T. Holgersson, Peter S. Karlsson May 2010

Model Based Vs. Model Independent Tests For Cross-Correlation, H.E.T. Holgersson, Peter S. Karlsson

Journal of Modern Applied Statistical Methods

This article discusses the issue of whether cross correlation should be tested by model dependent or model independent methods. Several different tests are proposed and their main properties are investigated analytically and with simulations. It is argued that model independent tests should be used in applied work.

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On Exact 100(1-Α)% Confidence Interval Of Autocorrelation Coefficient In Multivariate Data When The Errors Are Autocorrelated, Madhusudan Bhandary May 2010

On Exact 100(1-Α)% Confidence Interval Of Autocorrelation Coefficient In Multivariate Data When The Errors Are Autocorrelated, Madhusudan Bhandary

Journal of Modern Applied Statistical Methods

An exact 100(1−α)% confidence interval for the autocorrelation coefficient ρ is derived based on a single multinormal sample. The confidence interval is the interval between the two roots of a quadratic equation in ρ . A real life example is also presented.

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The Performance Of Multiple Imputation For Likert-Type Items With Missing Data, Walter Leite, S. Natasha Beretvas May 2010

The Performance Of Multiple Imputation For Likert-Type Items With Missing Data, Walter Leite, S. Natasha Beretvas

Journal of Modern Applied Statistical Methods

The performance of multiple imputation (MI) for missing data in Likert-type items assuming multivariate normality was assessed using simulation methods. MI was robust to violations of continuity and normality. With 30% of missing data, MAR conditions resulted in negatively biased correlations. With 50% missingness, all results were negatively biased.

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Median-Unbiased Optimal Smoothing And Trend Extraction, Dimitrios D. Thomakos May 2010

Median-Unbiased Optimal Smoothing And Trend Extraction, Dimitrios D. Thomakos

Journal of Modern Applied Statistical Methods

The problem of smoothing a time series for extracting its low frequency characteristics, collectively called its trend, is considered. A competitive approach is proposed and compared with existing methods in choosing the optimal degree of smoothing based on the distribution of the residuals from the smooth trend.

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On A Comparison Between Two Measures Of Spatial Association, Faisal G. Khamis, Abdul Aziz Jemain, Kamarulzaman Ibrahim May 2010

On A Comparison Between Two Measures Of Spatial Association, Faisal G. Khamis, Abdul Aziz Jemain, Kamarulzaman Ibrahim

Journal of Modern Applied Statistical Methods

Two measures of spatial association between two variables were used by many researchers. These are the Wartenberg (1985) and Lee (2001) measures. Based on simulation for lattice data, the sensitivity of both measures was studied and compared with different choices of spatial structures, spatial weights and sample sizes using bias and mean square error. Different scenarios are used in terms of assumed numbers and sample sizes. Moran’s I is used to examine the spatial autocorrelation of such a variable with itself. Both the Wartenberg and Lee measures are found to be sensitive, however, Wartenberg’s measure is found to be somewhat …

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An Evaluation Of Multiple Imputation For Meta-Analytic Structural Equation Modeling, Carolyn F. Furlow, S. Natasha Beretvas May 2010

An Evaluation Of Multiple Imputation For Meta-Analytic Structural Equation Modeling, Carolyn F. Furlow, S. Natasha Beretvas

Journal of Modern Applied Statistical Methods

A simulation study was used to evaluate multiple imputation (MI) to handle MCAR correlations in the first step of meta-analytic structural equation modeling: the synthesis of the correlation matrix and the test of homogeneity. No substantial parameter bias resulted from using MI. Although some SE bias was found for meta-analyses involving smaller numbers of studies, the homogeneity test was never rejected when using MI.

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Impact Of Measurement Model Modification On Structural Parameter Integrity When Measurement Model Is Misspecified, Weihua Fan May 2010

Impact Of Measurement Model Modification On Structural Parameter Integrity When Measurement Model Is Misspecified, Weihua Fan

Journal of Modern Applied Statistical Methods

In the process of model modification, parameters of residual covariances are often treated as free parameters to improve model fit. However, the effect of such measurement model modifications on the important structural parameter estimates under various measurement model misspecifications has not been systematically studied. Monte Carlo simulation was conducted to compare structural estimates before and after measurement model modifications of adding residual covariances under varying sample sizes and model misspecifications. Results showed that researchers should pay attention when such measurement model modifications are made to initially misspecified model with missing path(s).

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