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Articles 751 - 780 of 1395
Full-Text Articles in Applied Statistics
Steady State Probabilities Of A Three Preemptive Single Server Queue, Ameen Jameel Alawneh
Steady State Probabilities Of A Three Preemptive Single Server Queue, Ameen Jameel Alawneh
Journal of Modern Applied Statistical Methods
A three preemptive priority queuing system is considered where customers with three priorities joined a queue according to a Poisson process. A customer with higher priority needs to enter the service immediately upon arrival. The recursive formulas approach was extended to determine the steady state probabilities of such a priority queuing system.
Estimation Of Multinomial Proportions Using Higher Order Moments Of Scrambling Variables In Randomized Response Sampling, Cheng C. Chen, Sarjinder Singh
Estimation Of Multinomial Proportions Using Higher Order Moments Of Scrambling Variables In Randomized Response Sampling, Cheng C. Chen, Sarjinder Singh
Journal of Modern Applied Statistical Methods
An extension to estimating multinomial proportions of potentially sensitive attributes in survey sampling is proposed using higher order moments of scrambling variables at the estimation stage to produce unbiased estimators. The variance and covariance expressions are derived and the relative efficiency of the proposed estimators based on scrambling variables is investigated.
Inverted Exponential Distribution Under A Bayesian Viewpoint, Gyan Prakash
Inverted Exponential Distribution Under A Bayesian Viewpoint, Gyan Prakash
Journal of Modern Applied Statistical Methods
The objective of this study was to examine the properties of Bayes estimators of the parameter, reliability function and hazard rate under the symmetric and asymmetric loss functions for the inverted exponential model. The Bayes predictive interval and the Bayes estimate of shift point are also determined. A simulation study was carried out to study the properties of the Bayes estimators.
Underlying Distributions In Loglinear Models Of Discrete Data, Tim Moses
Underlying Distributions In Loglinear Models Of Discrete Data, Tim Moses
Journal of Modern Applied Statistical Methods
The implications of loglinear models based on underlying uniform and binomial distribution are assessed with respect to modeling eight distributions. Regarding statistical selection of the loglinear models’ parameterizations, results indicate that better fitting models are obtained when the distribution being modeled is dissimilar to the underlying distribution used. For loglinear models with predetermined numbers of parameters, results suggest that better fitting models can be obtained when the distribution being modeled is similar to the underlying distribution.
Robust Modifications Of The Levene And O’Brien Tests For Spread, Abdul R. Othman, The Sin Yan, H. J. Keselman, Rand R. Wilcox, James Algina
Robust Modifications Of The Levene And O’Brien Tests For Spread, Abdul R. Othman, The Sin Yan, H. J. Keselman, Rand R. Wilcox, James Algina
Journal of Modern Applied Statistical Methods
Variants of Levene’s and O’Brien’s procedures not investigated by Keselman, Wilcox & Algina (2008) were examined. Simulations indicate that a new O’Brien variant provides very good Type I error control and is simpler for applied researchers to compute than the method recommended by Keselman, et al.
An Extension Of The Seasonal Kpss Test, Sami Khedhiri, Ghassen El Montasser
An Extension Of The Seasonal Kpss Test, Sami Khedhiri, Ghassen El Montasser
Journal of Modern Applied Statistical Methods
The limit theory of the seasonal KPSS test is established under the null hypothesis using seasonal dummy variables. Taking these variables into account can result in improved finite sample performance of the test. The seasonal KPSS test can be interpreted as a test of deterministic seasonality and it may be used in addition to seasonal unit root tests to analyze the dynamic properties of time series. The seasonal indicator variables provide the test with an explicit model-based regression that in itself constitutes a support for its limit theory.
Improved Estimator In The Presence Of Multicollinearity, Ghadban Khalaf
Improved Estimator In The Presence Of Multicollinearity, Ghadban Khalaf
Journal of Modern Applied Statistical Methods
The performances of two biased estimators for the general linear regression model under conditions of collinearity are examined and a new proposed ridge parameter is introduced. Using Mean Square Error (MSE) and Monte Carlo simulation, the resulting estimator’s performance is evaluated and compared with the Ordinary Least Square (OLS) estimator and the Hoerl and Kennard (1970a) estimator. Results of the simulation study indicate that, with respect to MSE criteria, in all cases investigated the proposed estimator outperforms both the OLS and the Hoerl and Kennard estimators.
The Weighted Hellinger Distance For Kernel Distribution Estimator Of Function Of Observations, Abdel-Razzaq Mugdadi
The Weighted Hellinger Distance For Kernel Distribution Estimator Of Function Of Observations, Abdel-Razzaq Mugdadi
Journal of Modern Applied Statistical Methods
The asymptotic mean weighted Hellinger distance (AMWHD) is derived for the kernel distribution estimator of a function of observations. In addition, the AMWHD is compared with the asymptotic mean integrated square error (AMISE) of the estimator. A completely data based method is proposed to select the bandwidth in the estimator using the mean weighted Hellinger distance (MWHD).
Toward A Regional Radiocarbon Model For The East Texas Woodland Period, Robert Z. Selden Jr., Timothy K. Perttula
Toward A Regional Radiocarbon Model For The East Texas Woodland Period, Robert Z. Selden Jr., Timothy K. Perttula
CRHR: Archaeology
The East Texas Radiocarbon Database contributes to an analysis of tempo and place for Woodland era (ca. 500 B.C. - A.D. 800) archaeological sites within the region. The temporal and spatial distributions of calibrated radiocarbon (14C) ages (n=127) with a standard deviation (ΔT) of 61 from archaeological sites with Woodland components (n=51) are useful in exploring the development and geographical continuity of the peoples in East Texas, and lead to a refinement of our current chronological understanding of the period. While the analysis of the dates produces less than significant findings due to sample size, they are used …
Modeling Regional Radicarbon Trends: A Case Study From The East Texas Woodland Period, Robert Z. Selden Jr.
Modeling Regional Radicarbon Trends: A Case Study From The East Texas Woodland Period, Robert Z. Selden Jr.
CRHR: Archaeology
The East Texas Radiocarbon Database contributes to an analysis of tempo and place for Woodland era (~500 BC–AD 800) archaeological sites within the region. The temporal and spatial distributions of calibrated 14C ages (n = 127) with a standard deviation (ΔT) of 61 from archaeological sites with Woodland components (n = 51) are useful in exploring the development and geographical continuity of the peoples in east Texas, and lead to a refinement of our current chronological understanding of the period. While analysis of summed probability distributions (SPDs) produces less than significant findings due to sample size, they are used …
The East Texas Caddo: Modeling Tempo And Place, Robert Z. Selden Jr., Timothy K. Perttula
The East Texas Caddo: Modeling Tempo And Place, Robert Z. Selden Jr., Timothy K. Perttula
CRHR: Archaeology
Analysis of the Caddo sample (n=889 dates) from the East Texas radiocarbon database is used to establish the tempo and place of Caddo era (ca. A.D. 800-1680) archaeological sites, site clusters, and communities across the region. The temporal and spatial distribution of radiocarbon ages from settlements, mound centers, and cemeteries across the region have utility in exploring the development and geographical continuity of the Caddo peoples; establishing the specific times when areas were abandoned or population sizes diminished; and defining times and areas illustrating an intensification in mound center construction and large cemeteries became a focus of community social practices.
Analysis Of Discrete Choice Probit Models With Structured Correlation Matrices, Bhaskara Ravi
Analysis Of Discrete Choice Probit Models With Structured Correlation Matrices, Bhaskara Ravi
Mathematics & Statistics Theses & Dissertations
Discrete choice models are very popular in Economics and the conditional logit model is the most widely used model to analyze consumer choice behavior, which was introduced in a seminal paper by McFadden (1974). This model is based on the assumption that the unobserved factors, which determine the consumer choices, are independent and follow a Gumbel distribution, widely known as the Independence of irrelevant Alternatives (IIA) assumption. Alternate models that relax IIA assumption are the Generalized Extreme Value (GEV) models, which allow dependency between unobserved factors. However, GEV models do not incorporate all dependency patterns, other choice behaviors such as …
Spatial Analysis Of Fatal Automobile Crashes In Kentucky, William Nathan Oris
Spatial Analysis Of Fatal Automobile Crashes In Kentucky, William Nathan Oris
Masters Theses & Specialist Projects
Fatal automobile crashes have claimed the lives of over 33,000 people each year in the United States since 1995. As in any point event, fatal crash events do not occur randomly in time or space. The objectives of this study were to identify spatial patterns and hot spots in FARS (Fatal Analysis Reporting System) fatal crash events based on temporal and demographic characteristics. The methods employed included 1) rate calculation using FARS points and average daily traffic flow; 2) planar kernel density estimation of FARS crash events based on temporal and demographic attributes within the data; and 3) two case …
Contributions Of Financial Sector Reforms And Credit Supply To Nigerian Agricultural Sector (1978-2009), Anthony O. Onoja, M. E. Onu, S. Ajodo-Ohiemi
Contributions Of Financial Sector Reforms And Credit Supply To Nigerian Agricultural Sector (1978-2009), Anthony O. Onoja, M. E. Onu, S. Ajodo-Ohiemi
CBN Journal of Applied Statistics (JAS)
This study analyzed the trends and pattern of institutional credit supply to agriculture during pre- and post-financial reforms along with their determinants. It then compared the effects of reform policies on access to institutional credits in Nigerian agricultural sector before and after the reforms (1978 - 1985; and 1986 -2009). Relying mainly on time series data from CBN and NBS, it used ordinary least squares method (linear, semi-log and double log) to model the determinants of banking sector lending to the agricultural sector during the review period. The models were subjected to several econometric tests before accepting one. Chow test …
Determinants Of Foreign Reserves In Nigeria: An Autoregressive Distributed Lag Approach, David Irefin, Baba N. Yaaba
Determinants Of Foreign Reserves In Nigeria: An Autoregressive Distributed Lag Approach, David Irefin, Baba N. Yaaba
CBN Journal of Applied Statistics (JAS)
On global scale, central banks’ holdings of foreign reserves have escalated sharply in recent years. World international reserves holdings have risen significantly from US$1.2 trillion in 1995 to nearly US$10.0 trillion in June 2011. Dominant among these reserves are concentrated in the hands of few countries. Ten major holders of foreign reserves are mostly from Asia. Oil exporting countries in Africa and the Middle East are not left out in this trend. Nigeria’s foreign reserves rose from US$5.5 billion in 1999 to US$62.40 billion in July 2008, making Nigeria the twenty-fourth largest reserves holder in the world. This pace of …
Effects Of Exchange Rate Movements On Economic Growth In Nigeria, Eme O. Akpan, Johnson A. Atan
Effects Of Exchange Rate Movements On Economic Growth In Nigeria, Eme O. Akpan, Johnson A. Atan
CBN Journal of Applied Statistics (JAS)
This study investigates the effect of exchange rate movements on real output growth in Nigeria. Based on quarterly series for the period 1986 to 2010, the paper examines the possible direct and indirect relationship between exchange rates and GDP growth. The relationship is derived in two ways using a simultaneous equations model within a fully specified (but small) macroeconomic model. A Generalised Method of Moments (GMM) technique was explored. The estimation results suggest that there is no evidence of a strong direct relationship between changes in exchange rate and output growth. Rather, Nigeria’s economic growth has been directly affected by …
Exchange Rate Volatility In Nigeria: Consistency, Persistency & Severity Analyses, Babatunde Adeoye, Akinwande A. Atanda
Exchange Rate Volatility In Nigeria: Consistency, Persistency & Severity Analyses, Babatunde Adeoye, Akinwande A. Atanda
CBN Journal of Applied Statistics (JAS)
The adoption of the International Monetary Fund (IMF) Structural Adjustment Programme (SAP) in 1986 resulted in the transition from fixed exchange rate regime to floating exchange rate regime in Nigeria. Ever since, the exchange rate of naira vis-à-vis the U.S dollar has attained varying rates all through different time horizons. On this basis, this study examines the consistency, persistency, and severity (degree) of volatility in exchange rate of Nigerian currency (naira) vis-a-vis the United State dollar using monthly time series data from 1986 to 2008. The standard Purchasing Power Parity (PPP) model was used to analyze the long-run consistency of …
Foreign Private Investment And Economic Growth In Nigeria: A Cointegrated Var And Granger Causality Analysis, F. Z. Abdullahi, S. Ladan, Haruna R. Bakari
Foreign Private Investment And Economic Growth In Nigeria: A Cointegrated Var And Granger Causality Analysis, F. Z. Abdullahi, S. Ladan, Haruna R. Bakari
CBN Journal of Applied Statistics (JAS)
This research uses a cointegration VAR model to study the contemporaneous long-run dynamics of the impact of Foreign Private Investment (FPI), Interest Rate (INR) and Inflation rate (IFR) on Growth Domestic Products (GDP) in Nigeria for the period January 1970 to December 2009. The Unit Root Test suggests that all the variables are integrated of order 1. The VAR model was appropriately identified using AIC information criteria and the VECM model has exactly one cointegration relation. The study further investigates the causal relationship using the Granger causality analysis of VECM which indicates a uni-directional causality relationship between GDP and FDI …
Banking Sector Credit And Economic Growth In Nigeria: An Empirical Investigation, Aniekan O. Akpansung, Sikiru J. Babalola
Banking Sector Credit And Economic Growth In Nigeria: An Empirical Investigation, Aniekan O. Akpansung, Sikiru J. Babalola
CBN Journal of Applied Statistics (JAS)
The paper examines the relationship between banking sector credit and economic growth in Nigeria over the period 1970-2008. The causal links between the pairs of variables of interest were established using Granger causality test while a Two-Stage Least Squares (TSLS) estimation technique was used for the regression models. The results of Granger causality test show evidence of unidirectional causal relationship from GDP to private sector credit (PSC) and from industrial production index (IND) to GDP. Estimated regression models indicate that private sector credit impacts positively on economic growth over the period of coverage in this study. However, lending (interest) rate …
Neither The Washington Nor Beijing Consensus: Developmental Models To Fit African Realities And Cultures, Sanusi L. Sanusi
Neither The Washington Nor Beijing Consensus: Developmental Models To Fit African Realities And Cultures, Sanusi L. Sanusi
CBN Journal of Applied Statistics (JAS)
No abstract provided.
Comparison Of Several Tests For Combining Several Independent Tests, Madhusudan Bhandary, Xuan Zhang
Comparison Of Several Tests For Combining Several Independent Tests, Madhusudan Bhandary, Xuan Zhang
Journal of Modern Applied Statistical Methods
Several tests for combining p-values from independent tests have been considered to address a particular common testing problem. A simulation study shows that Fisher’s (1932) Inverse Chi-square test is optimal based on a power comparison of several different tests.
Discriminant Analysis For Repeated Measures Data: Effects Of Mean And Covariance Misspecification On Bias And Error In Discriminant Function Coefficients, Tolulope T. Sajobi, Lisa M. Lix, Longhai Li, William Laverty
Discriminant Analysis For Repeated Measures Data: Effects Of Mean And Covariance Misspecification On Bias And Error In Discriminant Function Coefficients, Tolulope T. Sajobi, Lisa M. Lix, Longhai Li, William Laverty
Journal of Modern Applied Statistical Methods
Discriminant analysis (DA) procedures based on parsimonious mean and/or covariance structures have been proposed for repeated measures (RM) data. Bias and means square error of discriminant function coefficients (DFCs) for DA procedures are investigated when the mean and/or covariance structures are correctly specified and misspecified.
Construction Of Control Charts Based On Six Sigma Initiatives For The Number Of Defects And Average Number Of Defects Per Unit, R. Radhakrishnan, P. Balamurugan
Construction Of Control Charts Based On Six Sigma Initiatives For The Number Of Defects And Average Number Of Defects Per Unit, R. Radhakrishnan, P. Balamurugan
Journal of Modern Applied Statistical Methods
A control chart is a statistical device used for the study and control of a repetitive process. In 1931, Shewart suggested control charts based on 3 sigma limits. Today manufacturing companies around the world apply Six Sigma initiatives, with a result offewer product defects. Companies practicing Six Sigma initiatives are expected to produce 3.4 or less number of defects per million opportunities, a concept suggested by Motorola in 1980. If companies practicing Six Sigma initiatives use control limits suggested by Shewhart, then no points will fall outside the control limits due to the improvement in the quality of the process. …
Identification Of Optimal Autoregressive Integrated Moving Average Model On Temperature Data, Olusola Samuel Makinde, Olusoga Akin Fasoranbaku
Identification Of Optimal Autoregressive Integrated Moving Average Model On Temperature Data, Olusola Samuel Makinde, Olusoga Akin Fasoranbaku
Journal of Modern Applied Statistical Methods
Autoregressive Integrated Moving Average (ARIMA) processes of various orders are presented to identify an optimal model from a class of models. Parameters of the models are estimated using an Ordinary Least Square (OLS) approach. ARIMA (p, d, q) is formulated for maximum daily temperature data in Ondo and Zaira from January 1995 to November 2005. The choice of ARIMA models of orders p and q is intended to retain persistence in a natural process. To determine the performance of models, Normalized Bayesian Information Criterion is adopted. The ARIMA (1, 1, 1) is adequate for modeling maximum daily temperature in Ondo …
Height-Diameter Relationship In Tree Modeling Using Simultaneous Equation Techniques In Correlated Normal Deviates, S. O. Oyamakin
Height-Diameter Relationship In Tree Modeling Using Simultaneous Equation Techniques In Correlated Normal Deviates, S. O. Oyamakin
Journal of Modern Applied Statistical Methods
In other to study the complex simultaneous relationships existing in forest/tree growth modeling, six estimation methods of a simultaneous equation model are examined to determine how they cope with varying degrees of correlation between pairs of random deviates using average parameter estimates. A two-equation simultaneous system assumed covariance matrix was considered. The model was structured to have a mutual correlation between pairs of random deviates: a violation of the assumption of mutual independence between pairs of such random deviates. The correlation between the pairs of normal deviates were generated using three scenarios r = 0.0, 0.3 and 0.5. The performances …
Tests For Correlation On Bivariate Non-Normal Data, L. Beversdorf, Ping Sa
Tests For Correlation On Bivariate Non-Normal Data, L. Beversdorf, Ping Sa
Journal of Modern Applied Statistical Methods
Two statistics are considered to test the population correlation for non-normally distributed bivariate data. A simulation study shows that both statistics control type I error rates well for left-tailed tests and have reasonable power performance.
Lq-Moments For Regional Flood Frequency Analysis: A Case Study For The North-Bank Region Of The Brahmaputra River, India, Abhijit Bhuyan, Munindra Borah
Lq-Moments For Regional Flood Frequency Analysis: A Case Study For The North-Bank Region Of The Brahmaputra River, India, Abhijit Bhuyan, Munindra Borah
Journal of Modern Applied Statistical Methods
The LQ-moment proposed by Mudholkar, et al. (1998) is used for regional flood frequency analysis of the North-Bank region of the river Brahmaputra, India. Five probability distributions are used for the LQmoment: generalized extreme value (GEV), generalized logistic (GLO) and generalized Pareto (GPA), lognormal (LN3) and Pearson Type III (PE3). The same regional frequency analysis procedure proposed by Hosking (1990) for the L-moment is used for the LQ-moment. Based on the LQ-moment ratio diagram and |Zidist| -statistic criteria, the PE3 distribution is identified as the robust distribution for the study area. For estimation of floods of various …
Explicit Equations For Acf In Autoregressive Processes In The Presence Of Heteroscedasticity Disturbances, Samir Safi
Explicit Equations For Acf In Autoregressive Processes In The Presence Of Heteroscedasticity Disturbances, Samir Safi
Journal of Modern Applied Statistical Methods
The autocorrelation function, ACF, is an important guide to the properties of a time series. Explicit equations are derived for ACF in the presence of heteroscedasticity disturbances in pth order autoregressive, AR(p), processes. Two cases are presented: (1) when the disturbance term follows the general covariance matrix, Σ , and (2) when the diagonal elements of Σ are not all identical but σi,j = 0 ∀i ≠ j.
Type I Error Rates Of The Two-Sample Pseudo-Median Procedure, Nor Aishah Ahad, Abdul Rahman Othman, Sharipah Soaad Syed Yahaya
Type I Error Rates Of The Two-Sample Pseudo-Median Procedure, Nor Aishah Ahad, Abdul Rahman Othman, Sharipah Soaad Syed Yahaya
Journal of Modern Applied Statistical Methods
The performance of the pseudo-median based procedure is examined in terms of controlling Type I error for a two independent groups test. The procedure is a modification of the one-sample Wilcoxon statistic using the pseudo-median of differences between group values as the central measure of location. The proposed procedure was shown to have good control of Type I error rates under the study conditions regardless of distribution type.
Modified Ratio And Product Estimators For Population Mean In Systematic Sampling, Housila P. Singh, Rajesh Tailor, Narendra Kumar Jatwa
Modified Ratio And Product Estimators For Population Mean In Systematic Sampling, Housila P. Singh, Rajesh Tailor, Narendra Kumar Jatwa
Journal of Modern Applied Statistical Methods
The estimation of population mean in systematic sampling is explored. Properties of a ratio and product estimator that have been suggested in systematic sampling are investigated, along with the properties of double sampling. Following Swain (1964), the cost aspect is also discussed.