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1,633 full-text articles. Page 32 of 45.

Parameter Estimation Of A Class Of Hidden Markov Model With Diagnostics, E. B. Nkemnole, O. Abass, R. A. Kasumu 2013 University of Lagos, Nigeria, Africa

Parameter Estimation Of A Class Of Hidden Markov Model With Diagnostics, E. B. Nkemnole, O. Abass, R. A. Kasumu

Journal of Modern Applied Statistical Methods

A stochastic volatility (SV) problem is formulated as a state space form of a Hidden Markov model (HMM). The SV model assumes that the distribution of asset returns conditional on the latent volatility is normal. This article analyzes the SV model with the student-t distribution and the generalized error distribution (GED) and compares these distributions with a mixture of normal distributions from Kim and Stoffer (2008). A Sequential Monte Carlo with Expectation Maximization (SMCEM) algorithm technique was used to estimate parameters for the extended volatility model; the Akaike Information Criteria (AIC) and forecast statistics were calculated to compare distribution fit. …


Estimation And Testing In Type I Generalized Half Logistic Distribution, R. R. L. Kantam, V. Ramakrishna, M. S. Ravikumar 2013 AcharyaNagarjuna University, Nagarjunanagar, India

Estimation And Testing In Type I Generalized Half Logistic Distribution, R. R. L. Kantam, V. Ramakrishna, M. S. Ravikumar

Journal of Modern Applied Statistical Methods

A generalization of the half logistic distribution is developed through exponentiation of its cumulative distribution function and termed the Type I Generalized Half Logistic Distribution (GHLD). GHLD’s distributional characteristics and parameter estimation using maximum likelihood and modified maximum likelihood methods are presented with comparisons. Comparison of Type I GHLD and the exponential distribution is conducted via likelihood ratio criterion.


P-Values Versus Significance Levels, Phillip I. Good 2013 Information Research, Huntington Beach, CA

P-Values Versus Significance Levels, Phillip I. Good

Journal of Modern Applied Statistical Methods

In this article Phillip Good responds to Richard Anderson's article Conceptual Distinction between the Critical p Value and the Type I Error Rate in Permutation Testing.


Randomization Test P-Values Versus Significance Levels, Bryan Manly 2013 Western EcoSystem Technology, Inc., Cheyenne, WY

Randomization Test P-Values Versus Significance Levels, Bryan Manly

Journal of Modern Applied Statistical Methods

Bryan Manly responds to Richard Anderson's article Conceptual Distinction between the Critical p Value and the Type I Error Rate in Permutation Testing.


Conceptual Distinction Between The Critical P Value And The Type I Error Rate In Permutation Testing: Author Response To Peer Comments, Richard B. Anderson 2013 Bowling Green State University

Conceptual Distinction Between The Critical P Value And The Type I Error Rate In Permutation Testing: Author Response To Peer Comments, Richard B. Anderson

Journal of Modern Applied Statistical Methods

Richard Anderson responds to comments regarding his target article Conceptual Distinction between the Critical p Value and the Type I Error Rate in Permutation Testing.


Estimation Of Variance Using Known Coefficient Of Variation And Median Of An Auxiliary Variable, J. Subramani, G. Kumarapandiyan 2013 Pondicherry University

Estimation Of Variance Using Known Coefficient Of Variation And Median Of An Auxiliary Variable, J. Subramani, G. Kumarapandiyan

Journal of Modern Applied Statistical Methods

A modified ratio type variance estimator for estimating population variance of a study variable when the population median and coefficient of variation of an auxiliary variable are known is proposed. The bias and mean squared error of the proposed estimator are derived and conditions under which the proposed estimator performs better than the traditional ratio type variance estimators and modified ratio type variance estimators are obtained. Using a numerical study results show that the proposed estimator performs better than the traditional ratio type variance estimator and existing modified ratio type variance estimators.


Priorities In Thurstone Scaling And Steady-State Probabilities In Markov Stochastic Modeling, Stan Lipovetsky 2013 GfK Custom Research North America, Minneapolis, MN

Priorities In Thurstone Scaling And Steady-State Probabilities In Markov Stochastic Modeling, Stan Lipovetsky

Journal of Modern Applied Statistical Methods

Thurstone scaling is widely used in marketing and advertising research where various methods of applied psychology are utilized. This article considers several analytical tools useful for positioning a set of items on a Thurstone scale via regression modeling and Markov stochastic processing in the form of Chapman-Kolmogorov equations. These approaches produce interval and ratio scales of preferences and enrich the possibilities of paired comparison estimation applied for solving practical problems of prioritization and probability of choice modeling.


On The Gamma-Half Normal Distribution And Its Applications, Ayman Alzaatreh, Kristen Knight 2013 Austin Peay State University, Clarksville, TN

On The Gamma-Half Normal Distribution And Its Applications, Ayman Alzaatreh, Kristen Knight

Journal of Modern Applied Statistical Methods

A new distribution, the gamma-half normal distribution, is proposed and studied. Various structural properties of the gamma-half normal distribution are derived. The shape of the distribution may be unimodal or bimodal. Results for moments, limit behavior, mean deviations and Shannon entropy are provided. To estimate the model parameters, the method of maximum likelihood estimation is proposed. Three real-life data sets are used to illustrate the applicability of the gamma-half normal distribution.


The Length-Biased Versus Random Sampling For The Binomial And Poisson Events, Makarand V. Ratnaparkhi, Uttara V. Naik-Nimbalkar 2013 Wright State University

The Length-Biased Versus Random Sampling For The Binomial And Poisson Events, Makarand V. Ratnaparkhi, Uttara V. Naik-Nimbalkar

Journal of Modern Applied Statistical Methods

The equivalence between the length-biased and the random sampling on a non-negative, discrete random variable is established. The length-biased versions of the binomial and Poisson distributions are discussed.


Improved Estimators In Finite Population Surveys: Theory And Applications, Sunil Kumar 2013 SOSU, Indian Statistical Institute - Kolkata

Improved Estimators In Finite Population Surveys: Theory And Applications, Sunil Kumar

Journal of Modern Applied Statistical Methods

Improved estimators are proposed for estimating the population mean of the study variable y using auxiliary variable x in simple random sampling. Explicit expression for the bias and MSE of the proposed family are derived to the first order of approximation. The proposed estimators are compared with other estimators and theoretical findings are illustrated by two numerical examples.


An Approach For Dealing With Statuses Of Non-Statistically Significant Interactions Between Treatments, Zakaria M. Sawan 2013 Cotton Research Institute, Giza, Egypt

An Approach For Dealing With Statuses Of Non-Statistically Significant Interactions Between Treatments, Zakaria M. Sawan

Journal of Modern Applied Statistical Methods

A field experiment on cotton yield resulted in a non-statistically significant interaction. An approach for follow-up examination between treatments based on least significant difference values was suggested to identify the effect regardless of insignificance. It was found that the classical formula used in calculating the significance of interactions suffers a possible shortage that can be eliminated by applying a suggested revision.


Conceptual Distinction Between The Critical P Value And The Type I Error Rate In Permutation Testing, Richard B. Anderson 2013 Bowling Green State University

Conceptual Distinction Between The Critical P Value And The Type I Error Rate In Permutation Testing, Richard B. Anderson

Journal of Modern Applied Statistical Methods

To counter past assertions that permutation testing is not distribution-free, this article clarifies that the critical p value (alpha) in permutation testing is not a Type I error rate and that a test's validity is independent of the concept of Type I error.


A Response To Anderson's (2013) Conceptual Distinction Between The Critical P Value And Type I Error Rate In Permutation Testing, Fortunato Pesarin, Stefano Bonnini 2013 University of Padova, Italy

A Response To Anderson's (2013) Conceptual Distinction Between The Critical P Value And Type I Error Rate In Permutation Testing, Fortunato Pesarin, Stefano Bonnini

Journal of Modern Applied Statistical Methods

Pesarin and Bonnini respond to Anderson's (2013) Conceptual Distinction between the Critical p value and Type I Error Rate in Permutation Testing


A Monte Carlo Simulation Of The Robust Rank-Order Test Under Various Population Symmetry Conditions, William T. Mickelson 2013 University of Wisconsin - Whitewater

A Monte Carlo Simulation Of The Robust Rank-Order Test Under Various Population Symmetry Conditions, William T. Mickelson

Journal of Modern Applied Statistical Methods

The Type I Error Rate of the Robust Rank Order test under various population symmetry conditions is explored through Monte Carlo simulation. Findings indicate the test has difficulty controlling Type I error under generalized Behrens-Fisher conditions for moderately sized samples.


Constructing A More Powerful Test In Two-Level Block Randomized Designs, Spyros Konstantopoulos 2013 Michigan State University

Constructing A More Powerful Test In Two-Level Block Randomized Designs, Spyros Konstantopoulos

Journal of Modern Applied Statistical Methods

A more powerful test is proposed for the treatment effect in two-level block randomized designs where random assignment takes place at the first level. When clustering at the second level is assumed to be known, the proposed test produces higher estimates of power than the typical test.


Bayesian Inference Of Pair-Copula Constriction For Multivariate Dependency Modeling Of Iran’S Macroeconomic Variables, M. R. Zadkarami, O. Chatrabgoun 2013 ShahidChamran University, Ahvaz, Iran

Bayesian Inference Of Pair-Copula Constriction For Multivariate Dependency Modeling Of Iran’S Macroeconomic Variables, M. R. Zadkarami, O. Chatrabgoun

Journal of Modern Applied Statistical Methods

Bayesian inference of pair-copula constriction (PCC) is used for multivariate dependency modeling of Iran’s macroeconomics variables: oil revenue, economic growth, total consumption and investment. These constructions are based on bivariate t-copulas as building blocks and can model the nature of extreme events in bivariate margins individually. The model parameter was estimated based on Markov chain Monte Carlo (MCMC) methods. A MCMC algorithm reveals unconditional as well as conditional independence in Iran’s macroeconomic variables, which can simplify resulting PCC’s for these data.


Using The Bootstrap For Estimating The Sample Size In Statistical Experiments, Maher Qumsiyeh 2013 University of Dayton

Using The Bootstrap For Estimating The Sample Size In Statistical Experiments, Maher Qumsiyeh

Journal of Modern Applied Statistical Methods

Efron’s (1979) Bootstrap has been shown to be an effective method for statistical estimation and testing. It provides better estimates than normal approximations for studentized means, least square estimates and many other statistics of interest. It can be used to select the active factors - factors that have an effect on the response - in experimental designs. This article shows that the bootstrap can be used to determine sample size or the number of runs required to achieve a certain confidence level in statistical experiments.


The X-Alter Algorithm: A Parameter-Free Method Of Unsupervised Clustering, Thomas Laloë, Rémi Servien 2013 Université of Nice Sophia-Antipolis, Nice, France

The X-Alter Algorithm: A Parameter-Free Method Of Unsupervised Clustering, Thomas Laloë, Rémi Servien

Journal of Modern Applied Statistical Methods

Using quantization techniques, Laloë (2010) defined a new clustering algorithm called Alter. This L1-based algorithm is shown to be convergent but suffers two major flaws. The number of clusters, K, must be supplied by the user and the computational cost is high. This article adapts the X-means algorithm (Pelleg & Moore, 2000) to solve both problems.


Estimating Heterogeneous Intra-Class Correlation Coefficients In Dyadic Ecological Momentary Assessment, Emily A. Blood, Leslie A. Kalish, Lydia A. Shrier 2013 Boston Children’s Hospital, Department of Pediatrics, Harvard Medical School

Estimating Heterogeneous Intra-Class Correlation Coefficients In Dyadic Ecological Momentary Assessment, Emily A. Blood, Leslie A. Kalish, Lydia A. Shrier

Journal of Modern Applied Statistical Methods

A method is described for estimating and testing predictors for influence on the variance of momentary behaviors in dyadic ecological momentary assessment data. Results show that the method allows intraclass correlations of momentary observations from two members of the same couple to vary by observation-level, individual-level and couple-level predictors.


Jmasm 32: Multiple Imputation Of Missing Multilevel, Longitudinal Data: A Case When Practical Considerations Trump Best Practices?, Jennifer E. V. Lloyd, Jelena Obradović, Richard M. Carpiano, Frosso Motti-Stefanidi 2013 University of British Columbia

Jmasm 32: Multiple Imputation Of Missing Multilevel, Longitudinal Data: A Case When Practical Considerations Trump Best Practices?, Jennifer E. V. Lloyd, Jelena Obradović, Richard M. Carpiano, Frosso Motti-Stefanidi

Journal of Modern Applied Statistical Methods

A pedagogical tool is presented for applied researchers dealing with incomplete multilevel, longitudinal data. It explains why such data pose special challenges regarding missingness. Syntax created to perform a multiply-imputed growth modeling procedure in Stata Version 11 (StataCorp, 2009) is also described.


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