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Articles 721 - 750 of 1395
Full-Text Articles in Applied Statistics
Weighted Cook-Johnson Copula And Their Characterizations: Application To Probably Modeling Of The Hot Spring Eruptions, Hakim Bekrizadeh, Gholam Ali Parham, Mohamd Reza Zadkarmi
Weighted Cook-Johnson Copula And Their Characterizations: Application To Probably Modeling Of The Hot Spring Eruptions, Hakim Bekrizadeh, Gholam Ali Parham, Mohamd Reza Zadkarmi
Journal of Modern Applied Statistical Methods
Copulas have emerged as a practical method for multivariate modeling. A limited amount of work has been conducted regarding the application of copula-based modeling in context analysis. This study generalizes the Cook-Johnson copula under the appropriate weighted function and provides examples and the properties of the generalized Cook-Johnson copula. Results show that the generalized Cook-Johnson copula is suitable for probable modeling of hot spring eruption.
Comparing Two Independent Groups Via A Quantile Generalization Of The Wilcoxon-Mann-Whitney Test, Rand R. Wilcox
Comparing Two Independent Groups Via A Quantile Generalization Of The Wilcoxon-Mann-Whitney Test, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
The Wilcoxon-Mann-Whitney test, as well as modern improvements, are based in part on an estimate of p = P(D < 0), where D = X−Y and X and Y are independent random variables; a common goal is to test H0: p = 0.5. This corresponds to testing H0: ξ0.5, where ξ0.5 is the 0.5 quantile of the distribution of D. If the distributions associated with X and Y do not differ, then D has a symmetric distribution about zero. In particular, ξq + ξ1-q = 0 for any q ≤ 0.5, where ξq is the qth quantile. Methods aimed at testing H0: p = 0.5 are generalized by …
Single Sampling Plans For Variables Indexed By Aql And Aoql With Measurement Error, R. Sankle, J.R. Singh
Single Sampling Plans For Variables Indexed By Aql And Aoql With Measurement Error, R. Sankle, J.R. Singh
Journal of Modern Applied Statistical Methods
Single sampling plans are investigated for variables indexed by acceptable quality level (AQL) and average outgoing quality limit (AOQL) under measurement error. Procedures and tables are provided for selection of single sampling plans for variables for given AQL and AOQL when rejected lots are 100% inspected for replacement of a nonconforming unit. For a particular sampling plan in operation for an observed measurement, a method for determining true operating characteristic (OC) functions and average outgoing quality (AOQ) is described for various error sizes.
An Extension Of Cochran-Orcutt Procedure For Generalized Linear Regression Models With Periodically Correlated Errors, Abdullah A. Smadi, Nour H. Abu-Afouna
An Extension Of Cochran-Orcutt Procedure For Generalized Linear Regression Models With Periodically Correlated Errors, Abdullah A. Smadi, Nour H. Abu-Afouna
Journal of Modern Applied Statistical Methods
An important assumption of ordinary regression models is independence among errors. This research considers the case of periodically correlated errors following the periodic AR model of order 1 (PAR(1)). The remedial measure for correlated errors in regression known as the Cochran-Orcutt procedure is generalized to the case of periodically correlated errors. The motivation for making such generalizations is that the response data may inhibit some seasonality, which may not be captured by the traditional AR(1) autoregressive model. The proposed procedure is described and the bias and MSE of the resulting intercept and slope parameter estimates of the simple LR model …
A Proposed Ridge Parameter To Improve The Least Square Estimator, Ghadban Khalaf
A Proposed Ridge Parameter To Improve The Least Square Estimator, Ghadban Khalaf
Journal of Modern Applied Statistical Methods
Ridge regression, a form of biased linear estimation, is a more appropriate technique than ordinary least squares (OLS) estimation in the case of highly intercorrelated explanatory variables in the linear regression model Y = β + u. Two proposed ridge regression parameters from the mean square error (MSE) perspective are evaluated. A simulation study was conducted to demonstrate the performance of the proposed estimators compared to the OLS, HK and HKB estimators. Results show that the suggested estimators outperform the OLS and the other estimators regarding the ridge parameters in all situations examined.
Graphical Modeling For High Dimensional Data, Munni Begum, Jay Bagga, C. Ann Blakey
Graphical Modeling For High Dimensional Data, Munni Begum, Jay Bagga, C. Ann Blakey
Journal of Modern Applied Statistical Methods
With advances in science and information technologies, many scientific fields are able to meet the challenges of managing and analyzing high-dimensional data. A so-called large p small n problem arises when the number of experimental units, n, is equal to or smaller than the number of features, p. A methodology based on probability and graph theory, termed graphical models, is applied to study the structure and inference of such high-dimensional data.
A Graphical Examination Of Variable Deletion Within The Mewma Statistic, Jay R. Schaffer, Shawn Vandenhul
A Graphical Examination Of Variable Deletion Within The Mewma Statistic, Jay R. Schaffer, Shawn Vandenhul
Journal of Modern Applied Statistical Methods
A general procedure for identifying the variable(s) that contribute(s) to the signal of the multivariate extension of the exponentially weighted moving average (MEWMA) chart is presented. The procedure systematically removes one or two variables from the MEWMA statistic calculations. Percentages are calculated for correctly identifying various shifts.
Testing The Population Coefficient Of Variation, Shipra Banik, B. M. Golam Kibria, Dinesh Sharma
Testing The Population Coefficient Of Variation, Shipra Banik, B. M. Golam Kibria, Dinesh Sharma
Journal of Modern Applied Statistical Methods
The coefficient of variation (CV), which is used in many scientific areas, measures the variability of a population relative to its mean and standard deviation. Several methods exist for testing the population CV. This article compares a proposed bootstrap method to existing methods. A simulation study was conducted under both symmetric and skewed distributions to compare the performance of test statistics with respect to empirical size and power. Results indicate that some of the proposed methods are useful and can be recommended to practitioners.
Bayesian Estimation Of Erlang Distribution Under Different Generalized Truncated Distributions As Priors, Adil H. Khan, T.R. Jan
Bayesian Estimation Of Erlang Distribution Under Different Generalized Truncated Distributions As Priors, Adil H. Khan, T.R. Jan
Journal of Modern Applied Statistical Methods
Various generalized truncated distributions are considered as independent informative priors for estimating shape and scale parameters of the Erlang distribution. In addition, various special cases are also discussed.
Multivariate Generalized Poisson Distribution For Interference On Selected Non-Communicable Diseases In Lagos State, Nigeria, Adewara Johnson Ademola, Mbata Ugochuckwu Ahamefula
Multivariate Generalized Poisson Distribution For Interference On Selected Non-Communicable Diseases In Lagos State, Nigeria, Adewara Johnson Ademola, Mbata Ugochuckwu Ahamefula
Journal of Modern Applied Statistical Methods
Multivariate Generalized Poisson Distribution (MGPD) models are applied to make inferences regarding non-communicable diseases, diabetes, hypertension, stroke and ulcer in Lagos State, Nigeria. The generalized Poisson distribution is employed due to its usefulness in modeling count data in the presence of either over- or under- dispersion. Results show that the correlation between ulcer and stroke is not significant. Other pairwise comparisons of diseases are significant, thus implying that a patient who suffers from diabetes or stroke has a high propensity to also be hypertensive.
Ferrieri's Index Of Openness Applied To Remittances To Developing Countries, Gaetano Ferrieri
Ferrieri's Index Of Openness Applied To Remittances To Developing Countries, Gaetano Ferrieri
Journal of Modern Applied Statistical Methods
A new methodology to measure international openness and globalization is described. This allows capacity to be effectively combined with size in a number of socio-economic areas, such as trade, migration and foreign investment. The method is applied to remittances to developing countries.
Analysis Of Bank Failure And Size Of Assets, Guancun Zhong
Analysis Of Bank Failure And Size Of Assets, Guancun Zhong
UNLV Theses, Dissertations, Professional Papers, and Capstones
The financial health of the banking industry is an important prerequisite for economic stability and growth. Bank failures in the United States have run in cycles largely associated with the collapse of economic bubbles. The number of bank failures has increased dramatically over the last thirty years (Halling and Hayden, 2007). In this thesis, we try to address the following two questions: 1) What is the relationship, if any, between a bank's asset size and its likelihood of failures? 2) How can we use statistical tools to predict the numbers of bank failures in the future? Various modeling techniques are …
The Impact Of Violating Factor Scaling Method Assumptions On Latent Mean Difference Testing In Structured Means Models, Dandan Wang, Tiffany A. Whittaker, S. Natasha Beretvas
The Impact Of Violating Factor Scaling Method Assumptions On Latent Mean Difference Testing In Structured Means Models, Dandan Wang, Tiffany A. Whittaker, S. Natasha Beretvas
Journal of Modern Applied Statistical Methods
Type I error rates and power of the likelihood ratio test and bias of the standardized effect size measure associated with the latent mean difference in structured means modeling are examined when violating the assumptions underlying the two available factor scaling methods under various conditions. Implications and recommendations are discussed.
New Approximate Bayesian Confidence Intervals For The Coefficient Of Variation Of A Gaussian Distribution, Vincent A. R. Camara
New Approximate Bayesian Confidence Intervals For The Coefficient Of Variation Of A Gaussian Distribution, Vincent A. R. Camara
Journal of Modern Applied Statistical Methods
Confidence intervals are constructed for the coefficient of variation of a Gaussian distribution. Considering the square error and the Higgins-Tsokos loss functions, approximate Bayesian models are derived and compared to a published classical model. The models are shown to have great coverage accuracy. The classical model does not always yield the best confidence intervals; the proposed models often perform better.
A Poisson Regression Model For Female Radium Dial Workers, Tze-San Lee
A Poisson Regression Model For Female Radium Dial Workers, Tze-San Lee
Journal of Modern Applied Statistical Methods
A Poisson regression model with interaction terms was applied to study the dose response relationship for radium-induced skeletal cancers. The model showed that the expected frequency count of bone tumors depended not only on the logarithmic dose and the time since first exposure, but also on the interaction between the logarithmic dose and the time since first exposure, whereas the dose-response model for head tumors depended only on the logarithmic dose.
Jmasm 32: Sas Template For Single-Subject Experimental Designs, Hyewon Chung, Jiseon Kim, Ryoungsun Park
Jmasm 32: Sas Template For Single-Subject Experimental Designs, Hyewon Chung, Jiseon Kim, Ryoungsun Park
Journal of Modern Applied Statistical Methods
Meta-analysis has been used to synthesize research findings and to evaluate the effectiveness of treatments or the accuracy of diagnostic tools. Although meta-analytic techniques were developed to synthesize the results of several studies, controversy exists as to how to quantify the results from singlesubject experimental designs (SSEDs). The most commonly used metrics are reviewed, including nonregression and regression based methods. The application of the SAS template is demonstrated through simulated data sets. The SAS templates can be modified to accommodate a more complex data structure.
The Length-Biased Lognormal Distribution And Its Application In The Analysis Of Data From Oil Field Exploration Studies, Makarand V. Ratnaparkhi, Uttara V. Naik-Nimbalkar
The Length-Biased Lognormal Distribution And Its Application In The Analysis Of Data From Oil Field Exploration Studies, Makarand V. Ratnaparkhi, Uttara V. Naik-Nimbalkar
Journal of Modern Applied Statistical Methods
The length-biased version of the lognormal distribution and related estimation problems are considered and sized-biased data arising in the exploration of oil fields is analyzed. The properties of the estimators are studied using simulations and the use of sample mode as an estimate of the lognormal parameter is discussed.
Four Period Crossover Designs, James F. Reed Iii
Four Period Crossover Designs, James F. Reed Iii
Journal of Modern Applied Statistical Methods
In higher-order four period crossover designs with two treatments, sixteen possible treatment sequences can result: AAAA, AAAB, AABA, AABB, ABAA, ABAB, ABBA, ABBB and their duals. Higher-order crossover designs are useful for several reasons: they allow estimation of a treatment effect even in the presence of a carry-over effect, they provide estimates of intra-subject variability and they draw inference on the carry-over effect. The real question related to a two-treatment four-period crossover design is the real world application of these designs. This article considers four designs: Design I: ABBA and its dual; Design II: ABBA, AABB and their duals, Design …
Gamma-Pareto Distribution And Its Applications, Ayman Alzaatreh, Felix Famoye, Carl Lee
Gamma-Pareto Distribution And Its Applications, Ayman Alzaatreh, Felix Famoye, Carl Lee
Journal of Modern Applied Statistical Methods
A new distribution, the gamma-Pareto, is defined and studied and various properties of the distribution are obtained. Results for moments, limiting behavior and entropies are provided. The method of maximum likelihood is proposed for estimating the parameters and the distribution is applied to fit three real data sets.
A Weighted Exponential Detection Function Model For Line Transect Data, Faisal Ababneh, Omar M. Eidous
A Weighted Exponential Detection Function Model For Line Transect Data, Faisal Ababneh, Omar M. Eidous
Journal of Modern Applied Statistical Methods
A new parametric model is proposed for modeling the density function of perpendicular distances in line transects sampling. The model can be considered a weighted exponential model in the sense that it combines two exponential models with different weights. The proposed model is appealing because it is monotone decreasing with distance from transect line; in contrast to the classical exponential model, it satisfies the shoulder condition at the origin. Simulation results for a wide range of target densities show reasonable and good performances of the weighted exponential model in most considered cases compared to the classical exponential and the half-normal …
Ordinal Regression Analysis: Using Generalized Ordinal Logistic Regression Models To Estimate Educational Data, Xing Liu, Hari Koirala
Ordinal Regression Analysis: Using Generalized Ordinal Logistic Regression Models To Estimate Educational Data, Xing Liu, Hari Koirala
Journal of Modern Applied Statistical Methods
The proportional odds (PO) assumption for ordinal regression analysis is often violated because it is strongly affected by sample size and the number of covariate patterns. To address this issue, the partial proportional odds (PPO) model and the generalized ordinal logit model were developed. However, these models are not typically used in research. One likely reason for this is the restriction of current statistical software packages: SPSS cannot perform the generalized ordinal logit model analysis and SAS requires data restructuring. This article illustrates the use of generalized ordinal logistic regression models to predict mathematics proficiency levels using Stata and compares …
Robust Regression Estimates In The Prediction Of Latent Variables In Structural Equation Models, Marcelo Angelo Cirillo, Lúcia Pereira Barroso
Robust Regression Estimates In The Prediction Of Latent Variables In Structural Equation Models, Marcelo Angelo Cirillo, Lúcia Pereira Barroso
Journal of Modern Applied Statistical Methods
The incorporation of the robust regression methods Least Median Square (LMS) and Least Trimmed Squares (LTS) is proposed in structural equation modeling. Results show that, in situations of high deviations of symmetry, the evaluated methods would be recommended for applications including smaller sample sizes.
Comparison Of Re-Sampling Methods To Generalized Linear Models And Transformations In Factorial And Fractional Factorial Designs, Maher Qumsiyeh, Gerald Shaughnessy
Comparison Of Re-Sampling Methods To Generalized Linear Models And Transformations In Factorial And Fractional Factorial Designs, Maher Qumsiyeh, Gerald Shaughnessy
Journal of Modern Applied Statistical Methods
Experimental situations in which observations are not normally distributed frequently occur in practice. A common situation occurs when responses are discrete in nature, for example counts. One way to analyze such experimental data is to use a transformation for the responses; another is to use a link function based on a generalized linear model (GLM) approach. Re-sampling is employed as an alternative method to analyze non-normal, discrete data. Results are compared to those obtained by the previous two methods.
Statistical Inferences For Lomax Distribution Based On Record Values (Bayesian And Classical), Parviz Nasiri, Saman Hosseini
Statistical Inferences For Lomax Distribution Based On Record Values (Bayesian And Classical), Parviz Nasiri, Saman Hosseini
Journal of Modern Applied Statistical Methods
A maximum likelihood estimation (MLE) based on records is obtained and a proper prior distribution to attain a Bayes estimation (both informative and non-informative) based on records for quadratic loss and squared error loss functions is also calculated. The study considers the shortest confidence interval and Highest Posterior Distribution confidence interval based on records, and using Mean Square Error MSE criteria for point estimation and length criteria for interval estimation, their appropriateness to each other is examined.
Empirical Sampling From Permutation Space With Unique Patterns, Justice I. Odiase
Empirical Sampling From Permutation Space With Unique Patterns, Justice I. Odiase
Journal of Modern Applied Statistical Methods
The exact distribution of a test statistic ultimately guarantees that the probability of a Type I error is exactly α. Several methods for estimating the exact distribution of a test statistic have evolved over the years with inherent computational problems and varying degrees of accuracy. The unique pattern of permutations resulting from using experimental data to sample within the permutation space without the risk of repeating permutations is identified. The method presented circumvents the theoretical requirements of asymptotic procedures and the computational difficulties associated with an exhaustive enumeration of permutations. Results show that time and space complexities are drastically reduced …
Weight: Does It Really Matter?, Jennifer L. Brown, Gerald Halpin, Glennelle Halpin
Weight: Does It Really Matter?, Jennifer L. Brown, Gerald Halpin, Glennelle Halpin
Journal of Modern Applied Statistical Methods
Differential weighting promises to improve the validity of a measure. This study examines whether similar results would be found using weighted, unweighted and standardized z scores from the All Stars Core survey. It was concluded that the weighted systems were developed to equate the questions within the scales and to ease the process for customers without access to data analysis programs; however, the standardized scores were the more appropriate method for equating the test items.
Ratio Type Estimator Of Ratio Of Two Population Means In Stratified Random Sampling, Rajesh Tailor, Sunil Chouhan
Ratio Type Estimator Of Ratio Of Two Population Means In Stratified Random Sampling, Rajesh Tailor, Sunil Chouhan
Journal of Modern Applied Statistical Methods
A ratio estimator is proposed for the ratio of two population means using auxiliary information in stratified random sampling. Bias and mean squared error expressions are obtained under large sample approximation, and the proposed estimator is compared both theoretically and empirically with the conventional estimator of ratio for two population means in stratified random sampling.
Parameter Estimation With Mixture Item Response Theory Models: A Monte Carlo Comparison Of Maximum Likelihood And Bayesian Methods, W. Holmes Finch, Brian F. French
Parameter Estimation With Mixture Item Response Theory Models: A Monte Carlo Comparison Of Maximum Likelihood And Bayesian Methods, W. Holmes Finch, Brian F. French
Journal of Modern Applied Statistical Methods
The Mixture Item Response Theory (MixIRT) can be used to identify latent classes of examinees in data as well as to estimate item parameters such as difficulty and discrimination for each of the groups. Parameter estimation via maximum likelihood (MLE) and Bayesian estimation based on the Markov Chain Monte Carlo (MCMC) are compared for classification accuracy and parameter estimation bias for difficulty and discrimination. Standard error magnitude and coverage rates were compared across number of items, number of latent groups, group size ratio, total sample size and underlying item response model. Results show that MCMC provides more accurate group membership …
A Study On Underwriting Cycle Of Property Insurance Industry Of China, Lin Zhang, Linjuan Tang
A Study On Underwriting Cycle Of Property Insurance Industry Of China, Lin Zhang, Linjuan Tang
Journal of Modern Applied Statistical Methods
Methods in underwriting cycle research are compared. A second-order autoregressive model, which includes structural transition and Christiano-Fitzgerald (CF) Filter method, is used to analyze China’s underwriting cycle with annual property insurance loss ratio data from 1982 to 2008. Results show that the underwriting cycle is 11-12 years and, from the phase of underwriting cycle, management suggestions about underwriting cycle phenomenon are provided.
Regression Models For Mixed Over-Dispersed Poisson And Continuous Clustered Data: Modeling Bmi And Number Of Cigarettes Smoked Per Day, Folefac Atem, Julius S. Ngwa, Abidemi Adeniji
Regression Models For Mixed Over-Dispersed Poisson And Continuous Clustered Data: Modeling Bmi And Number Of Cigarettes Smoked Per Day, Folefac Atem, Julius S. Ngwa, Abidemi Adeniji
Journal of Modern Applied Statistical Methods
Clustered data, multiple observations collected on the same experimental unit, is common in epidemiological studies. Bivariate outcome data is often the result of interest in two correlated response variables. An efficient method is presented for dealing with bivariate outcomes when one outcome is continuous and the other is a count using a simple transformation to handle over-dispersed Poisson data. A multilevel analysis was performed on data from the National Health Interview Survey (NHIS) with body mass index (BMI) and the number of cigarettes smoked per day (NCS) as responses. Results show that these random effects models yield misleading results in …