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Articles 601 - 630 of 1191
Full-Text Articles in Statistical Theory
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 …
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.
Estimation Of Parameters Of Johnson’S System Of Distributions, Florence George, K. M. Ramachandran
Estimation Of Parameters Of Johnson’S System Of Distributions, Florence George, K. M. Ramachandran
Journal of Modern Applied Statistical Methods
Fitting distributions to data has a long history and many different procedures have been advocated. Although models like normal, log-normal and gamma lead to a wide variety of distribution shapes, they do not provide the degree of generality that is frequently desirable (Hahn & Shapiro, 1967). To formally represent a set of data by an empirical distribution, Johnson (1949) derived a system of curves with the flexibility to cover a wide variety of shapes. Methods available to estimate the parameters of the Johnson distribution are discussed, and a new approach to estimate the four parameters of the Johnson family is …
Robust Inference For Regression With Spatially Correlated Errors, Juchi Ou, Jeffrey M. Albert
Robust Inference For Regression With Spatially Correlated Errors, Juchi Ou, Jeffrey M. Albert
Journal of Modern Applied Statistical Methods
A robust variance estimator for a regression model with spatially correlated errors is proposed using the estimated empirical covariogram. Simulations studies show unbiasedness and robustness for the OLS but not for the GLS estimates. The new robust variance estimation method is applied to hospital quality data.. Stephanie A.
Maximum Log Likelihood Estimation Using Em Algorithm And Partition Maximum Log Likelihood Estimation For Mixtures Of Generalized Lambda Distributions, Steve Su
Journal of Modern Applied Statistical Methods
Two mixture distribution fitting methods based on maximizing the likelihood using generalized lambda distributions are presented. The fitting algorithms are demonstrated on various data and the strengths and weakness of the algorithms which can influence their use under different mixture modeling situations are discussed. The procedures described are available in GLDEX package in R.
A Sequential Monte Carlo Approach For Online Stock Market Prediction Using Hidden Markov Models, Ahani E. Bridget, O. Abass
A Sequential Monte Carlo Approach For Online Stock Market Prediction Using Hidden Markov Models, Ahani E. Bridget, O. Abass
Journal of Modern Applied Statistical Methods
A sequential Monte Carlo (SMC) algorithm prediction approach is developed based on joint probability distribution in hidden Markov Models (HMM). SMC methods, a general class of Monte Carlo methods, are typically used for sampling from sequences of distributions and simple examples of these algorithms are found extensively throughout the tracking and signal processing literature. Recent developments indicate that these techniques have much more general applicability and can be applied very effectively to statistical inference problems. Due to the problem involved in estimating the parameter of HMM, the HMM is represented in a state space model and the sequential Monte Carlo …
Jmasm31: Manova Procedure For Power Calculations (Spss), Alan Taylor
Jmasm31: Manova Procedure For Power Calculations (Spss), Alan Taylor
Journal of Modern Applied Statistical Methods
D’Amico, Neilands & Zambarano (2001) showed how the SPSS MANOVA procedure can be used to conduct power calculations for research designs. This article demonstrates a simple way of entering data required for power calculations into SPSS and provides examples that supplement those given by D’Amico, Neilands & Zambarano.
A Pooled Two-Sample Median Test Based On Density Estimation, Vadim Y. Bichutskiy
A Pooled Two-Sample Median Test Based On Density Estimation, Vadim Y. Bichutskiy
Journal of Modern Applied Statistical Methods
A new method based on density estimation is proposed for medians of two independent samples. The test controls the probability of Type I error and is at least as powerful as methods widely used in statistical practice. The method can be implemented using existing libraries in R.
Higher Order Markov Structure-Based Logistic Model And Likelihood Inference For Ordinal Data, Soma Chowdhury Biswas, M. Ataharul Islam, Jamal Nazrul Islam
Higher Order Markov Structure-Based Logistic Model And Likelihood Inference For Ordinal Data, Soma Chowdhury Biswas, M. Ataharul Islam, Jamal Nazrul Islam
Journal of Modern Applied Statistical Methods
Azzalini (1994) proposed a first order Markov chain for binary data. Azzalini’s model is extended for ordinal data and introduces a second order model. Further, the test statistics are developed and the power of the test is determined. An application using real data is also presented.
Robustness, Power And Interpretability Of Pairwise Tests Of Discriminant Functions In Manova, Philip H. Ramsey, Patricia P. Ramsey, Priscila Hachimine, Nancy Andiloro
Robustness, Power And Interpretability Of Pairwise Tests Of Discriminant Functions In Manova, Philip H. Ramsey, Patricia P. Ramsey, Priscila Hachimine, Nancy Andiloro
Journal of Modern Applied Statistical Methods
Limiting follow-up hypotheses to be tested can reduce problems relating to the control of Type I and Type II errors in multivariate analysis of variance (MANOVA). Such limitations can also improve the interpretability of results. The importance of sample size, shape of population distribution, within-group correlations and heterogeneity of variances are demonstrated. The protected greatest characteristic root (GCR) procedure is shown to work well for small, group size, N (≤ 10). The unprotected GCR is shown to work well for larger N.
A Comparison Of Factor Rotation Methods For Dichotomous Data, W. Holmes Finch
A Comparison Of Factor Rotation Methods For Dichotomous Data, W. Holmes Finch
Journal of Modern Applied Statistical Methods
Exploratory factor analysis (EFA) is frequently used in the social sciences and is a common component in many validity studies. A core aspect of EFA is the determination of which observed indicator variables are associated with which latent factors through the use of factor loadings. Loadings are initially extracted using an algorithm, such as maximum likelihood or weighted least squares, and then transformed - or rotated - to make them more interpretable. There are a number of rotational techniques available to the researcher making use of EFA. Prior work has discussed the advantages of a number of these criteria from …
Indeterminacy Of Factor Score Estimates In Slightly Misspecified Confirmatory Factor Models, André Beauducel
Indeterminacy Of Factor Score Estimates In Slightly Misspecified Confirmatory Factor Models, André Beauducel
Journal of Modern Applied Statistical Methods
Two methods to calculate a measure for the quality of factor score estimates have been proposed. These methods were compared by means of a simulation study. The method based on a covariance matrix reproduced from a model leads to smaller effects of sampling error.
Error Analysis On The Generalized Negative Binomial Distribution, Felix Famoye, Oluwakemi Aremu
Error Analysis On The Generalized Negative Binomial Distribution, Felix Famoye, Oluwakemi Aremu
Journal of Modern Applied Statistical Methods
The generalized negative binomial distribution characterized by three parameters, has been used to fit data from various fields of study. The distribution can model data for which the variance is larger or smaller than the mean, however, it becomes truncated under certain conditions. This truncation error is investigated via a detailed error analysis that determines the parameter space when the model can be used in place of the truncated generalized negative binomial distribution. The fitting of a generalized negative. K. M. Ramachandran is a
A Permutation Test For Compound Symmetry With Application To Gene Expression Data, Tracy L. Morris, Mark E. Payton, Stephanie A. Santorico
A Permutation Test For Compound Symmetry With Application To Gene Expression Data, Tracy L. Morris, Mark E. Payton, Stephanie A. Santorico
Journal of Modern Applied Statistical Methods
The development and application of a permutation test for compound symmetry is described. In a simulation study the permutation test appears to be a level-α test and is robust to non-normality. However, it exhibits poor power, particularly for small samples.
Ordinal Regression Analysis: Predicting Mathematics Proficiency Using The Continuation Ratio Model, Xing Liu, Ann A. O'Connell, Hari Koirala
Ordinal Regression Analysis: Predicting Mathematics Proficiency Using The Continuation Ratio Model, Xing Liu, Ann A. O'Connell, Hari Koirala
Journal of Modern Applied Statistical Methods
One commonly used model to analyze ordinal response data is the proportional odds (PO) model. However, if research interest is focused on a particular category and if an individual must pass through lower categories before achieving a higher level, the continuation ratio (CR) model is a more appropriate choice than the PO model. In addition, statistical software, such as Stata and SAS, may use different techniques to estimate the parameters. The CR model is used to illustrate the analysis of ordinal data in education using Stata and SAS and compares the results of fitting the CR model between these two …
Estimation And Hypothesis Testing In Lav Regression With Autocorrelated Errors: Is Correction For Autocorrelation Helpful?, Terry E. Dielman
Estimation And Hypothesis Testing In Lav Regression With Autocorrelated Errors: Is Correction For Autocorrelation Helpful?, Terry E. Dielman
Journal of Modern Applied Statistical Methods
Using the Prais-Winsten correction and adding a lagged variable provides improved estimates (smaller MSE) in least absolute value (LAV) regression when moderate to high levels of autocorrelation are present. When comparing empirical levels of significance for hypothesis tests, adding a lagged variable outperforms other approaches but has a relative high empirical level of significance.
Control Balanced Designs Involving Sequences Of Treatments, Cini Varghese, Seema Jaggi
Control Balanced Designs Involving Sequences Of Treatments, Cini Varghese, Seema Jaggi
Journal of Modern Applied Statistical Methods
Designs involving sequences of treatments for test vs. control comparisons are suitable for research in which each experimental unit receives treatments over time in order to compare several test treatments to one (or more) control treatment(s). These designs can be advantageously used in screening experiments and bioequivalence trials. Three series of such designs are constructed in incomplete sequences wherein the first class of designs is variance balanced while the other two classes of designs are partially variance balanced for test versus test comparisons of both direct and residual effects of treatments.
Probabilistic Inferences For The Sample Pearson Product Moment Correlation, Jeffrey R. Harring, John A. Wasko
Probabilistic Inferences For The Sample Pearson Product Moment Correlation, Jeffrey R. Harring, John A. Wasko
Journal of Modern Applied Statistical Methods
Fisher’s correlation transformation is commonly used to draw inferences regarding the reliability of tests comprised of dichotomous or polytomous items. It is illustrated theoretically and empirically that omitting test length and difficulty results in inflated Type I error. An empirically unbiased correction is introduced within the transformation that is applicable under any test conditions.
Non-Homogenous Poisson Process For Evaluating Stage I & Ii Ductal Breast Cancer Treatment, Chris P. Tsokos, Yong Xu
Non-Homogenous Poisson Process For Evaluating Stage I & Ii Ductal Breast Cancer Treatment, Chris P. Tsokos, Yong Xu
Journal of Modern Applied Statistical Methods
Non-Homogenous Poisson Process (NHPP), also known as the Power Law process (PLP) or the Weibull Process, is used to evaluate the effectiveness of a given treatment for Stage I & II ductal breast cancer patients. The behavior of the shape parameter of the intensity function is examined to evaluate the response of a given treatment with respect to its effectiveness for a cancer subject.