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Articles 1981 - 2010 of 2920
Full-Text Articles in Statistics and Probability
Can Specification Searches Be Useful For Hypothesis Generation?, Samuel B. Green, Marilyn S. Thompson
Can Specification Searches Be Useful For Hypothesis Generation?, Samuel B. Green, Marilyn S. Thompson
Journal of Modern Applied Statistical Methods
Previous studies suggest that results from specification searches, as typically employed in structural equation modeling, should not be used to reach strong research conclusions due to their poor reliability. Analyses of computer generated data indicate that search results can be sufficiently reliable for exploratory purposes with properly designed and analyzed studies.
Measuring Openness, Gaetano Ferrieri
Measuring Openness, Gaetano Ferrieri
Journal of Modern Applied Statistical Methods
A method for measuring international openness is elaborated. This synthetic indicator measures the capacity of countries for a given phenomenon adjusted for their weight in the same phenomenon. The method implemented and applied to international trade and illustrated here as a case study in merchandise exports, has a wide range of applications in the socio-economic field.
On The Appropriate Transformation Technique And Model Selection In Forecasting Economic Time Series: An Application To Botswana Gdp Data, D. K. Shangodoyin, K. Setlhare, K. K. Moseki, K. Sediakgotla
On The Appropriate Transformation Technique And Model Selection In Forecasting Economic Time Series: An Application To Botswana Gdp Data, D. K. Shangodoyin, K. Setlhare, K. K. Moseki, K. Sediakgotla
Journal of Modern Applied Statistical Methods
Selected data transformation techniques in time series modeling are evaluated using real-life data on Botswana Gross Domestic Product (GDP). The transformation techniques considered were modified, although reasonable estimates of the original with no significant difference at α = 0.05 level were obtained: minimizing square of first difference (MFD) and minimizing square of second difference (MSD) provided the best transformation for GDP, whereas the Goldstein and Khan (GKM) method had a deficiency of losing data points. The Box-Jenkins procedure was adapted to fit suitable ARIMA (p, d, q) models to both the original and transformed series, with AIC and SIC as …
A New Biased Estimator Derived From Principal Component Regression Estimator, Set Foong Ng, Heng Chin Low, Soon Hoe Quah
A New Biased Estimator Derived From Principal Component Regression Estimator, Set Foong Ng, Heng Chin Low, Soon Hoe Quah
Journal of Modern Applied Statistical Methods
A new biased estimator obtained by combining the Principal Component Regression Estimator and the special case of Liu-type estimator is proposed. The properties of the new estimator are derived and comparisons between the new estimator and other estimators in terms of mean squared error are presented.
Optimal Meter Placement By Reconciliation Conventional Measurements And Phasor Measurement Units (Pmus), Reza Kaihani, Ali Reza Seifi
Optimal Meter Placement By Reconciliation Conventional Measurements And Phasor Measurement Units (Pmus), Reza Kaihani, Ali Reza Seifi
Journal of Modern Applied Statistical Methods
The success of state estimation depends on the number, type and location of the established meters and RTUs on the system. A new method by incorporating conventional measurements and New Technology of Phasor Measurement Units (PMU) is proposed. Conventional meters (power injection and power flow measurements) are allocated in order to reduce the number of meters, RTUs, critical measurements, critical sets and leverage points, and also to improve the numerical stability of equations; a genetic algorithm is used for optimization. A second step involves adding PMUs in areas in which it is expected that the accuracy of state estimation will …
Fisher Was Right, Ronald C. Serlin
Fisher Was Right, Ronald C. Serlin
Journal of Modern Applied Statistical Methods
Invited address presented to the Educational Statistician’s Special Interest Group at the annual meeting of the American Educational Research Association, Denver, May 1, 2010.
Inferences About The Population Mean: Empirical Likelihood Versus Bootstrap-T, Rand R. Wilcox
Inferences About The Population Mean: Empirical Likelihood Versus Bootstrap-T, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
The problem of making inferences about the population mean, μ, is considered. Known theoretical results suggest that a Bartlett corrected empirical likelihood method is preferable to two basic bootstrap techniques: a symmetric two-sided bootstrap-t and an equal-tailed bootstrap-t. However, simulations in this study indicate that, when the sample size is small, these two bootstrap methods are generally better in terms of Type I errors and probability coverage. As the sample size increases, situations are found where the Bartlett corrected empirical likelihood method performs better than the equal-tailed bootstrap-t, but the symmetric bootstrap-t gives the best results. None of the four …
The Influence Of Data Generation On Simulation Study Results: Tests Of Mean Differences, Tim Moses, Alan Klockars
The Influence Of Data Generation On Simulation Study Results: Tests Of Mean Differences, Tim Moses, Alan Klockars
Journal of Modern Applied Statistical Methods
Type I error and power of the standard independent samples t-test were compared with the trimmed and Winsorized t-test with respect to continuous distributions and various discrete distributions known to occur in applied data. The continuous and discrete distributions were generated with similar levels of skew and kurtosis but the discrete distributions had a variety of structural features not reflected in the continuous distributions. The results showed that the Type I error rates of the t-tests were not seriously affected, but the power rate of the trimmed and Winsorized t-test varied greatly across the considered distributions.
The Small-Sample Efficiency Of Some Recently Proposed Multivariate Measures Of Location, Marie Ng, Rand R. Wilcox
The Small-Sample Efficiency Of Some Recently Proposed Multivariate Measures Of Location, Marie Ng, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
Numerous multivariate robust measures of location have been proposed and many have been found to be unsatisfactory in terms of their small-sample efficiency. Several new measures of location have recently been derived, however, nothing is known about their small-sample efficiency or how they compare to the sample mean under normality. This research compared the efficiency for p = 2, 5, and 8 with sample sizes n = 20 and 50 for p-variate data. Although previous studies indicate that so-called skipped estimators are efficient, this study found that variations of this approach can perform poorly when n is small and p …
Assessing Classification Bias In Latent Class Analysis: Comparing Resubstitution And Leave-One-Out Methods, Marc H. Kroopnick, Jinsong Chen, Jaehwa Choi, C. Mitchell Dayton
Assessing Classification Bias In Latent Class Analysis: Comparing Resubstitution And Leave-One-Out Methods, Marc H. Kroopnick, Jinsong Chen, Jaehwa Choi, C. Mitchell Dayton
Journal of Modern Applied Statistical Methods
This Monte Carlo simulation study assessed the degree of classification success associated with resubstitution methods in latent class analysis (LCA) and compared those results to those of the leaveone- out (L-O-O) method for computing classification success. Specifically, this study considered a latent class model with two classes, dichotomous manifest variables, restricted conditional probabilities for each latent class and relatively small sample sizes. The performance of resubstitution and L-O-O methods on the lambda classification index was assessed by examining the degree of bias.
Nonlinear Parameterization In Bi-Criteria Sample Balancing, Stan Lipovetsky
Nonlinear Parameterization In Bi-Criteria Sample Balancing, Stan Lipovetsky
Journal of Modern Applied Statistical Methods
Sample balancing is widely used in applied research to adjust a sample data to achieve better correspondence to Census statistics. The classic Deming-Stephan iterative proportional approach finds the weights of observations by fitting the cross-tables of sample counts to known margins. This work considers a bi-criteria objective for finding weights with maximum possible effective base size. This approach is presented as a ridge regression with the exponential nonlinear parameterization that produces nonnegative weights for sample balancing.
Jmasm30 Pi-Lca: A Sas Program Computing The Two-Point Mixture Index Of Fit For Two-Class Lca Models With Dichotomous Variables (Sas), Dongquan Zhang, C. Mitchell Dayton
Jmasm30 Pi-Lca: A Sas Program Computing The Two-Point Mixture Index Of Fit For Two-Class Lca Models With Dichotomous Variables (Sas), Dongquan Zhang, C. Mitchell Dayton
Journal of Modern Applied Statistical Methods
The two-point mixture index of fit enjoys some desirable features in model fit assessment and model selection, however, a need exists for efficient computational strategies. Applying an NLP algorithm, a program using the SAS matrix language is presented to estimate the two-point index of fit for two-class LCA models with dichotomous response variables. The program offers a tool to compute π ∗ for twoclass models and it also provides an alternative program for conducting latent class analysis with SAS. This study builds a foundation for further research on computational approaches for M-class models.
Another Look At Resampling: Replenishing Small Samples With Virtual Data Through S-Smart, Haiyan Bai, Wei Pan, Leigh Lihshing Wang, Phillip Neal Ritchey
Another Look At Resampling: Replenishing Small Samples With Virtual Data Through S-Smart, Haiyan Bai, Wei Pan, Leigh Lihshing Wang, Phillip Neal Ritchey
Journal of Modern Applied Statistical Methods
A new resampling method is introduced to generate virtual data through a smoothing technique for replenishing small samples. The replenished analyzable sample retains the statistical properties of the original small sample, has small standard errors and possesses adequate statistical power.
Estimations On The Generalized Exponential Distribution Using Grouped Data, Hassan Pazira, Parviz Nasiri
Estimations On The Generalized Exponential Distribution Using Grouped Data, Hassan Pazira, Parviz Nasiri
Journal of Modern Applied Statistical Methods
Classical and Bayesian estimators are obtained for the shape parameter of the Generalized-Exponential distribution under grouped data. In Bayesian estimation, three types of loss functions are considered: the Squared Error loss function which is classified as a symmetric function, the LINEX and Precautionary loss functions which are asymmetric. These estimators are compared with the corresponding estimators derived from un-grouped data empirically using Monte-Carlo simulation.
Symmetry Plus Quasi Uniform Association Model And Its Orthogonal Decomposition For Square Contingency Tables, Kouji Yamamoto, Sadao Tomizawa
Symmetry Plus Quasi Uniform Association Model And Its Orthogonal Decomposition For Square Contingency Tables, Kouji Yamamoto, Sadao Tomizawa
Journal of Modern Applied Statistical Methods
A model is proposed having the structure of both symmetry and quasi-uniform association (SQU model) and provides a decomposition of the SQU model. It is also shown with examples that the test statistic for goodness-of-fit of the SQU model is asymptotically equivalent to the sum of those for the decomposed models.
Applying Multiple Imputation With Geostatistical Models To Account For Item Nonresponse In Environmental Data, Breda Munoz, Virginia M. Lesser, Ruben A. Smith
Applying Multiple Imputation With Geostatistical Models To Account For Item Nonresponse In Environmental Data, Breda Munoz, Virginia M. Lesser, Ruben A. Smith
Journal of Modern Applied Statistical Methods
Methods proposed to solve the missing data problem in estimation procedures should consider the type of missing data, the missing data mechanism, the sampling design and the availability of auxiliary variables correlated with the process of interest. This article explores the use of geostatistical models with multiple imputation to deal with missing data in environmental surveys. The method is applied to the analysis of data generated from a probability survey to estimate Coho salmon abundance in streams located in western Oregon watersheds.
Beyond Alpha: Lower Bounds For The Reliability Of Tests, Nol Bendermacher
Beyond Alpha: Lower Bounds For The Reliability Of Tests, Nol Bendermacher
Journal of Modern Applied Statistical Methods
The most common lower bound to the reliability of a test is Cronbach’s alpha. However, several lower bounds exist that are definitely better, that is, higher than alpha. An overview is given as well as an algorithm to find the best: the greatest lower bound.
Shrinkage Estimation In The Inverse Rayleigh Distribution, Gyan Prakash
Shrinkage Estimation In The Inverse Rayleigh Distribution, Gyan Prakash
Journal of Modern Applied Statistical Methods
The properties of the shrinkage test–estimators of the parameter were studied for an inverse Rayleigh model under the asymmetric loss function. Both the single and double–stage shrinkage test–estimators are considered.
Combining Independent Tests Of Conditional Shifted Exponential Distribution, Abedel-Qader S. Al-Masri
Combining Independent Tests Of Conditional Shifted Exponential Distribution, Abedel-Qader S. Al-Masri
Journal of Modern Applied Statistical Methods
The problem of combining n independent tests as n→∞ for testing that variables are uniformly distributed over the interval (0, 1) compared to their having a conditional shifted exponential distribution with probability density function f (xθ ) = e−(x−γθ) , x ≥γθ , θ ∈[a,∞), a ≥ 0 was studied. This was examined for the case where θ1, θ2, … are distributed according to the distribution function (DF) F and when the DF is Gamma (1, 2). Six omnibus methods were compared via the Bahadur efficiency. It is shown that, as γ → 0 and …
A Comparative Study For Bandwidth Selection In Kernel Density Estimation, Omar M. Eidous, Mohammad Abd Alrahem Shafeq Marie, Mohammed H. Baker Al-Haj Ebrahem
A Comparative Study For Bandwidth Selection In Kernel Density Estimation, Omar M. Eidous, Mohammad Abd Alrahem Shafeq Marie, Mohammed H. Baker Al-Haj Ebrahem
Journal of Modern Applied Statistical Methods
Nonparametric kernel density estimation method does not make any assumptions regarding the functional form of curves of interest; hence it allows flexible modeling of data. A crucial problem in kernel density estimation method is how to determine the bandwidth (smoothing) parameter. This article examines the most important bandwidth selection methods, in particular, least squares cross-validation, biased crossvalidation, direct plug-in, solve-the-equation rules and contrast methods. Methods are described and expressions are presented. The main practical contribution is a comparative simulation study that aims to isolate the most promising methods. The performance of each method is evaluated on the basis of the …
On Construction Of The Smallest One-Sided Confidence Interval For The Difference Of Two Proportions, Weizhen Wang
On Construction Of The Smallest One-Sided Confidence Interval For The Difference Of Two Proportions, Weizhen Wang
Mathematics and Statistics Faculty Publications
For my class of one-sided 1 - α confidence intervals with a certain monotonicity ordering on the random confidence limit, the smallest interval, in the sense of the set inclusion for the difference of two proportions of two independent binomial random variables, is constructed based on a direct analysis of coverage probability function. A special ordering on the confidence limit is developed and the corresponding smallest confidence interval is derived. This interval is then applied to identify the minimum effective dose (MED) for binary data in dose-response studies, and a multiple test procedure that controls the familywise error rate at …
Rao's Quadratic Entropy And Some New Applications, Yueqin Zhao
Rao's Quadratic Entropy And Some New Applications, Yueqin Zhao
Mathematics & Statistics Theses & Dissertations
Many problems in statistical inference are formulated as testing the diversity of populations. The entropy functions measure the similarity of a distribution function to the uniform distribution and hence can be used as a measure of diversity. Rao (1982a) proposed the concept of quadratic entropy. Its concavity property makes the decomposition similar to ANOVA for categorical data feasible. In this thesis, after reviewing the properties and providing a modification to quadratic entropy, various applications of quadratic entropy are explored. First, analysis of quadratic entropy with the suggested modification to analyze the contingency table data is explored. Then its application to …
Knowing When To Say When: An Expanded Description Of Stopping Problems And Their Solutions, Eric C. Bauer
Knowing When To Say When: An Expanded Description Of Stopping Problems And Their Solutions, Eric C. Bauer
Mathematics
No abstract provided.
Augmenting Latent Dirichlet Allocation And Rank Threshold Detection With Ontologies, Laura A. Isaly
Augmenting Latent Dirichlet Allocation And Rank Threshold Detection With Ontologies, Laura A. Isaly
Theses and Dissertations
In an ever-increasing data rich environment, actionable information must be extracted, filtered, and correlated from massive amounts of disparate often free text sources. The usefulness of the retrieved information depends on how we accomplish these steps and present the most relevant information to the analyst. One method for extracting information from free text is Latent Dirichlet Allocation (LDA), a document categorization technique to classify documents into cohesive topics. Although LDA accounts for some implicit relationships such as synonymy (same meaning) it often ignores other semantic relationships such as polysemy (different meanings), hyponym (subordinate), meronym (part of), and troponomys (manner). To …
Monopoly, Regulation, And Innovation, Matt Bogard
Monopoly, Regulation, And Innovation, Matt Bogard
Economics Faculty Publications
Recently the Justice department has started investigations into alleged anti-trust violations by Monsanto. This has helped fuel a lot of already hyped discontent with one of the world’s leaders in innovative solutions for sustainable agriculture. This article discusses how the regulatory environment could possibly have contributed to more concentration and power in the biotech industry. Increasing regulation would likely have the opposite effect of creating a level playing field in the agriculture industry. From AgWeb, March 27,2010 http://www.agweb.com/blog/Economic_Sense_190/Monopoly_Regulation__and_Innovation_10771/
Software Internationalization: A Framework Validated Against Industry Requirements For Computer Science And Software Engineering Programs, John Huân Vũ
Master's Theses
View John Huân Vũ's thesis presentation at http://youtu.be/y3bzNmkTr-c.
In 2001, the ACM and IEEE Computing Curriculum stated that it was necessary to address "the need to develop implementation models that are international in scope and could be practiced in universities around the world." With increasing connectivity through the internet, the move towards a global economy and growing use of technology places software internationalization as a more important concern for developers. However, there has been a "clear shortage in terms of numbers of trained persons applying for entry-level positions" in this area. Eric Brechner, Director of Microsoft Development Training, suggested …
Applied Statistics: Experience & Cerification In Quality Assurance, Huey D. Dodson
Applied Statistics: Experience & Cerification In Quality Assurance, Huey D. Dodson
Statistics
The composition of my senior project can be broken down into two parts. The first part of my project, without which the second could not be pursued, involved a 13 week internship at a produce processing facility where I took part in several projects varying in scope and type. The second part was to acquire certification as a Quality Process Analyst from the American Society for Quality.
This document is structured to represent the dichotomous nature of my project; the first section is dedicated to my internship experience, and the second dedicated to the certification examination preparation and completion.
Integer Functions On The Cycle Space And Edges Of A Graph, Dan Slilaty
Integer Functions On The Cycle Space And Edges Of A Graph, Dan Slilaty
Mathematics and Statistics Faculty Publications
A directed graph has a natural Z-module homomorphism from the underlying graph’s cycle space to Z where the image of an oriented cycle is the number of forward edges minus the number of backward edges. Such a homomorphism preserves the parity of the length of a cycle and the image of a cycle is bounded by the length of that cycle. Pretzel and Youngs (SIAM J. Discrete Math. 3(4):544–553, 1990) showed that any Z-module homomorphism of a graph’s cycle space to Z that satisfies these two properties for all cycles must be such a map induced from an edge direction …
Electoral Voting And Population Distribution In The United States, Paul Kvam
Electoral Voting And Population Distribution In The United States, Paul Kvam
Department of Math & Statistics Faculty Publications
In the United States, the electoral system for determining the president is controversial and sometimes confusing to voters keeping track of election outcomes. Instead of directly counting votes to decide the winner of a presidential election, individual states send a representative number of electors to the Electoral College, and they are trusted to cast their collective vote for the candidate who won the popular vote in their state.
Under the current rules, the value of a vote differs from state to state. A large state such as California has an immense effect on the national election, but, compared to a …
Mathematical Themes In Economics, Machine Learning, And Bioinformatics, Matt Bogard
Mathematical Themes In Economics, Machine Learning, And Bioinformatics, Matt Bogard
Economics Faculty Publications
Graduate students in economics are often introduced to some very useful mathematical tools that many outside the discipline may not associate with training in economics. This essay looks at some of these tools and concepts, including constrained optimization, separating hyperplanes, supporting hyperplanes, and ‘duality.’ Applications of these tools are explored including topics from machine learning and bioinformatics.