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Full-Text Articles in Physical Sciences and Mathematics

Optimal Designs Approach To Portfolio Selection, Etukudo A. I. Dec 2010

Optimal Designs Approach To Portfolio Selection, Etukudo A. I.

CBN Journal of Applied Statistics (JAS)

In order to obtain the best tradeoff between risk and return, optimization algorithms are particularly useful in asset allocation in a portfolio mix. Such algorithms and proper solution techniques are very essential to investors in order to circumvent distress in business outfits. In this paper, we show that by minimizing the total variance of the portfolio involving stocks in two Nigerian banks which is a measure of risk, optimal allocation of investible funds to the portfolio mix is obtained. A completely new solution technique – modified super convergent line series algorithm which makes use of the principles of optimal designs …


Relationship Between Inflation And Stock Market Returns: Evidence From Nigeria, Omotor G. Douglason Dec 2010

Relationship Between Inflation And Stock Market Returns: Evidence From Nigeria, Omotor G. Douglason

CBN Journal of Applied Statistics (JAS)

The linkage between stock prices and inflation has been subjected to extensive research in the past decades and has arouse the interests of academics, researchers, practitioners and policy makers globally, particularly since the 1990s. The issue has been the apparent anomaly of the negative relationship between inflation and stock market returns as most studies in the industrialized economies have shown. This paper investigates this relationship using monthly and quarterly data of Nigeria for the period 1985 to 2008. The findings of this paper seem to suggest that stock market returns may provide an effective hedge against inflation in Nigeria.


Statistics For National Development, Sani I. Doguwa Dec 2010

Statistics For National Development, Sani I. Doguwa

CBN Journal of Applied Statistics (JAS)

Good statistics that has been collected according to agreed good practices are crucial as a tool for development. Gross domestic product (GDP) and other measures of economic activity such as Gross National Income (GNI) together with their individual components, show how the economy is responding to government policy and other influences. The balance of payments can demonstrate the requirement for policy adjustments and is also one of the indicators scrutinised by potential foreign investors in the country. Agricultural statistics clearly have implications for longer-term planning, particularly if they show a move away from the land into urban areas or a …


Monetary And Fiscal Policy Interactions In Nigeria: An Application Of A State-Space Model With Markov-Switching, Chuku V. Chuku Dec 2010

Monetary And Fiscal Policy Interactions In Nigeria: An Application Of A State-Space Model With Markov-Switching, Chuku V. Chuku

CBN Journal of Applied Statistics (JAS)

This paper uses quarterly data to explore the monetary and fiscal policy interactions in Nigeria between 1970 and 2008. As a preliminary exercise, the paper examines the nature of fiscal policies in Nigeria using a vector autoregression (VAR) model. The simulated generalized impulse response graphs generated from the VAR estimation provides evidence of a non-Ricardian fiscal policy in Nigeria. Further, the paper analyzes the interactions between monetary and fiscal policies by applying a State-space model with Markov-switching to estimate the time-varying parameters of the relationship. The evidence indicates that monetary and fiscal policies in Nigeria have interacted in a counteractive …


Is The Stock Market A Leading Indicator Of Economic Activity In Nigeria?, Alvan E. Ikoku Dec 2010

Is The Stock Market A Leading Indicator Of Economic Activity In Nigeria?, Alvan E. Ikoku

CBN Journal of Applied Statistics (JAS)

In an effort to address the lacuna in leading indicator studies of African economies and Nigeria in particular, this paper examines the causal relationships among stock market prices, real GDP and the index of industrial production in Nigeria, using quarterly data from 1984Q1 to 2008Q4. Granger causality tests indicate bidirectional causality between stock prices and GDP but no causality between stock prices and industrial production or between GDP and industrial production. Stock prices and GDP are found to be cointegrated, leading to the estimation of vector error correction models. Out-of-sample forecasts constructed with AR(1), ARIMA, structural ARIMA, and VEC models …


Factors, Preventions And Correction Methods For Non-Response In Sample Surveys, Godwin Nwanzu Amahi Dec 2010

Factors, Preventions And Correction Methods For Non-Response In Sample Surveys, Godwin Nwanzu Amahi

CBN Journal of Applied Statistics (JAS)

Missing survey data occur because of unit and item non-response. This is practically independent of the method of data collection. As a result of the bias that non-response sometimes introduces in survey estimates, identifying factors that promote it, and taking measures of prevention and correction methods are clearly necessary. The standard method to compensate for unit non-response is by weighting adjustment, while item non-responses are handled by some form of imputation. This paper reviews factors that give rise to nonresponse and the corresponding methods used for its prevention and control. It also discusses their properties.


Addressing The Problem Of Non-Response And Response Bias, Fabian C. Okafor Dec 2010

Addressing The Problem Of Non-Response And Response Bias, Fabian C. Okafor

CBN Journal of Applied Statistics (JAS)

Survey planners and analysts in Nigeria have devoted much more attention to sampling errors at the expense of nonsampling errors (non-response and response errors). Sampling error is the degree to which the sample estimate differs from the average value of the characteristic due to chance. The present discussion will be centered on non-sampling error, which may present serious deficiencies in the statistics and render the survey useless. According to Platek and Gray (1986), “Non-response has been generally recognized as important measure of the quality of data since it affects the estimates by introducing a possible bias in the estimates and …


A Multivariate Latent Variable Model For Mixed – Data From Continuous And Ordinal Responses With Possibility Of Missing Responses, Ehsan B. Samani, M. Ganjali Dec 2010

A Multivariate Latent Variable Model For Mixed – Data From Continuous And Ordinal Responses With Possibility Of Missing Responses, Ehsan B. Samani, M. Ganjali

Applications and Applied Mathematics: An International Journal (AAM)

A joint model for multivariate mixed ordinal and continuous outcomes with potentially non-random missing values in both types of responses is proposed. A full likelihood-based approach is used to obtain maximum likelihood estimates of the model parameters. Some modified Pearson residuals are also introduced where the correlation between responses are taken into account. The joint modelling of responses with the possibility of missing values requires caution since the interpretation of the fitted model highly depends on the missing mechanism assumptions that are unexaminable in a fundamental sense. A common way to investigate the influence of perturbations of model components on …


Approximate Approach To The Das Model Of Fractional Logistic Population Growth, S. Das, P. K. Gupta, K. Vishal Dec 2010

Approximate Approach To The Das Model Of Fractional Logistic Population Growth, S. Das, P. K. Gupta, K. Vishal

Applications and Applied Mathematics: An International Journal (AAM)

In this article, the analytical method, Homotopy perturbation method (HPM) has been successfully implemented for solving nonlinear logistic model of fractional order. The fractional derivatives are described in the Caputo sense. Using initial value, the explicit solutions of population size for different particular cases have been derived. Numerical results show that the method is extremely efficient to solve this complicated biological model.


Concomitants Of Upper Record Statistics For Bivariate Pseudo–Weibull Distribution, Muhammad Ahsanullah, Saman Shahbaz, Muhammad Qaiser Shahbaz, Muhammad Mohsin Dec 2010

Concomitants Of Upper Record Statistics For Bivariate Pseudo–Weibull Distribution, Muhammad Ahsanullah, Saman Shahbaz, Muhammad Qaiser Shahbaz, Muhammad Mohsin

Applications and Applied Mathematics: An International Journal (AAM)

In this paper the Bivariate Pseudo–Weibull distribution has been defined as a compound distribution of two random variables to model the failure rate of component reliability. The distribution of r–th concomitant and joint distribution of r–th and s–th concomitant of record statistics of the resulting distribution have been derived. Single and product moments alongside the correlation coefficient have also been obtained. Recurrence relation for the single moments has also been obtained for the resulting distributions.


Reliability Measures Of A Three-State Complex System: A Copula Approach, Mangey Ram Dec 2010

Reliability Measures Of A Three-State Complex System: A Copula Approach, Mangey Ram

Applications and Applied Mathematics: An International Journal (AAM)

Improvement in reliability and production play a very important role in system design. The two key factors, considered in predicting system reliability, are failure distribution of the component and system configuration. This research discusses the mathematical modeling of a highly reliable complex system, which is in three states i.e. normal, partial failed (degraded state) and complete failed state. The system, partial failed is due to the partial failure of internal components or redundancies and completely failed is due to catastrophic failure of the system. Repair rates are general functions of the time spent. All the transition rates are constant except …


A Flexible Method For Testing Independence In Two-Way Contingency Tables, Peyman Jafari, Noori Akhtar-Danesh, Zahra Bagheri Nov 2010

A Flexible Method For Testing Independence In Two-Way Contingency Tables, Peyman Jafari, Noori Akhtar-Danesh, Zahra Bagheri

Journal of Modern Applied Statistical Methods

A flexible approach for testing association in two-way contingency tables is presented. It is simple, does not assume a specific form for the association and is applicable to tables with nominal-by-nominal, nominal-by-ordinal, and ordinal-by-ordinal classifications.


The Not-So-Quiet Revolution: Cautionary Comments On The Rejection Of Hypothesis Testing In Favor Of A “Causal” Modeling Alternative, Daniel H. Robinson, Joel R. Levin Nov 2010

The Not-So-Quiet Revolution: Cautionary Comments On The Rejection Of Hypothesis Testing In Favor Of A “Causal” Modeling Alternative, Daniel H. Robinson, Joel R. Levin

Journal of Modern Applied Statistical Methods

Rodgers (2010) recently applauded a revolution involving the increased use of statistical modeling techniques. It is argued that such use may have a downside, citing empirical evidence in educational psychology that modeling techniques are often applied in cross-sectional, correlational studies to produce unjustified causal conclusions and prescriptive statements.


Statistical And Mathematical Modeling Versus Nhst? There’S No Competition!, Joseph Lee Rodgers Nov 2010

Statistical And Mathematical Modeling Versus Nhst? There’S No Competition!, Joseph Lee Rodgers

Journal of Modern Applied Statistical Methods

Some of Robinson & Levin’s critique of Rodgers (2010) is cogent, helpful, and insightful – although limiting. Recent methodology has advanced through the development of structural equation modeling, multi-level modeling, missing data methods, hierarchical linear modeling, categorical data analysis, as well as the development of many dedicated and specific behavioral models. These methodological approaches are based on a revised epistemological system, and have emerged naturally, without the need for task forces, or even much self-conscious discussion. The original goal was neither to develop nor promote a modeling revolution. That has occurred; I documented its development and its status. Two organizing …


Recommended Sample Size For Conducting Exploratory Factor Analysis On Dichotomous Data, Robert H. Pearson, Daniel J. Mundform Nov 2010

Recommended Sample Size For Conducting Exploratory Factor Analysis On Dichotomous Data, Robert H. Pearson, Daniel J. Mundform

Journal of Modern Applied Statistical Methods

Minimum sample sizes are recommended for conducting exploratory factor analysis on dichotomous data. A Monte Carlo simulation was conducted, varying the level of communalities, number of factors, variable-to-factor ratio and dichotomization threshold. Sample sizes were identified based on congruence between rotated population and sample factor loadings.


Notes On Hypothesis Testing Under A Single-Stage Design In Phase Ii Trial, Kung-Jong Lui Nov 2010

Notes On Hypothesis Testing Under A Single-Stage Design In Phase Ii Trial, Kung-Jong Lui

Journal of Modern Applied Statistical Methods

A primary objective of a phase II trial is to determine future development is warranted for a new treatment based on whether it has sufficient activity against a specified type of tumor. Limitations exist in the commonly-used hypothesis setting and the standard test procedure for a phase II trial. This study reformats the hypothesis setting to mirror the clinical decision process in practice. Under the proposed hypothesis setting, the critical points and the minimum required sample size for a desired power of finding a superior treatment at a given α -level are presented. An example is provided to illustrate how …


Effect Of Measurement Errors On The Separate And Combined Ratio And Product Estimators In Stratified Random Sampling, Housila P. Singh, Namrata Karpe Nov 2010

Effect Of Measurement Errors On The Separate And Combined Ratio And Product Estimators In Stratified Random Sampling, Housila P. Singh, Namrata Karpe

Journal of Modern Applied Statistical Methods

Separate and combined ratio, product and difference estimators are introduced for population mean μY of a study variable Y using auxiliary variable X in stratified sampling when the observations are contaminated with measurement errors. The bias and mean squared error of the proposed estimators have been derived under large sample approximation and their properties are analyzed. Generalized versions of these estimators are given along with their properties.


Use Of Two Variables Having Common Mean To Improve The Bar-Lev, Bobovitch And Boukai Randomized Response Model, Oluseun Odumade, Sarjinder Singh Nov 2010

Use Of Two Variables Having Common Mean To Improve The Bar-Lev, Bobovitch And Boukai Randomized Response Model, Oluseun Odumade, Sarjinder Singh

Journal of Modern Applied Statistical Methods

A new method to improve the randomized response model due to Bar-Lev, Bobovitch and Boukai (2004) is suggested. It has been observed that if two sensitive (or non sensitive) variables exist that are related to the main study sensitive variable, then those variables could be used to construct ratio type adjustments to the usual estimator of the population mean of a sensitive variable due to Bar-Lev, Bobovitch and Boukai (2004).The relative efficiency of the proposed estimators is studied with respect to the Bar-Lev, Bobovitch and Boukai (2004) models under different situations.


Incidence And Prevalence For A Triply Censored Data, Hilmi F. Kittani Nov 2010

Incidence And Prevalence For A Triply Censored Data, Hilmi F. Kittani

Journal of Modern Applied Statistical Methods

The model introduced for the natural history of a progressive disease has four disease states which are expressed as a joint distribution of three survival random variables. Covariates are included in the model using Cox’s proportional hazards model with necessary assumptions needed. Effects of the covariates are estimated and tested. Formulas for incidence in the preclinical, clinical and death states are obtained, and prevalence formulas are obtained for the preclinical and clinical states. Estimates of the sojourn times in the preclinical and clinical states are obtained.


Robust Estimators In Logistic Regression: A Comparative Simulation Study, Sanizah Ahmad, Norazan Mohamed Ramli, Habshah Midi Nov 2010

Robust Estimators In Logistic Regression: A Comparative Simulation Study, Sanizah Ahmad, Norazan Mohamed Ramli, Habshah Midi

Journal of Modern Applied Statistical Methods

The maximum likelihood estimator (MLE) is commonly used to estimate the parameters of logistic regression models due to its efficiency under a parametric model. However, evidence has shown the MLE has an unduly effect on the parameter estimates in the presence of outliers. Robust methods are put forward to rectify this problem. This article examines the performance of the MLE and four existing robust estimators under different outlier patterns, which are investigated by real data sets and Monte Carlo simulation.


A General Class Of Chain-Type Estimators In The Presence Of Non-Response Under Double Sampling Scheme, Sunil Kumar, Housila P. Singh, Sandeep Bhougal Nov 2010

A General Class Of Chain-Type Estimators In The Presence Of Non-Response Under Double Sampling Scheme, Sunil Kumar, Housila P. Singh, Sandeep Bhougal

Journal of Modern Applied Statistical Methods

General class chain ratio type estimators for estimating the population mean of a study variable are examined in the presence of non-response under a double sampling scheme using a factor-type estimator (FTE). Properties of the suggested estimators are studied and compared to those of existing estimators. An empirical study is carried out to demonstrate the performance of the suggested estimators; empirical results support the theoretical study.


Maximum Downside Semi Deviation Stochastic Programming For Portfolio Optimization Problem, Anton Abdulbasah Kamil, Khlipah Ibrahim Nov 2010

Maximum Downside Semi Deviation Stochastic Programming For Portfolio Optimization Problem, Anton Abdulbasah Kamil, Khlipah Ibrahim

Journal of Modern Applied Statistical Methods

Portfolio optimization is an important research field in financial decision making. The chief character within optimization problems is the uncertainty of future returns. Probabilistic methods are used alongside optimization techniques. Markowitz (1952, 1959) introduced the concept of risk into the problem and used a mean-variance model to identify risk with the volatility (variance) of the random objective. The mean-risk optimization paradigm has since been expanded extensively both theoretically and computationally. A single stage and two stage stochastic programming model with recourse are presented for risk averse investors with the objective of minimizing the maximum downside semideviation. The models employ the …


On Bayesian Shrinkage Setup For Item Failure Data Under A Family Of Life Testing Distribution, Gyan Prakash Nov 2010

On Bayesian Shrinkage Setup For Item Failure Data Under A Family Of Life Testing Distribution, Gyan Prakash

Journal of Modern Applied Statistical Methods

Properties of the Bayes shrinkage estimator for the parameter are studied of a family of probability density function when item failure data are available. The symmetric and asymmetric loss functions are considered for two different prior distributions. In addition, the Bayes estimates of reliability function and hazard rate are obtained and their properties are studied.


Empirical Characteristic Function Approach To Goodness Of Fit Tests For The Logistic Distribution Under Srs And Rss, M. T. Alodat, S. A. Al-Subh, Kamaruzaman Ibrahim, Abdul Aziz Jemain Nov 2010

Empirical Characteristic Function Approach To Goodness Of Fit Tests For The Logistic Distribution Under Srs And Rss, M. T. Alodat, S. A. Al-Subh, Kamaruzaman Ibrahim, Abdul Aziz Jemain

Journal of Modern Applied Statistical Methods

The integral of the squares modulus of the difference between the empirical characteristic function and the characteristic function of the hypothesized distribution is used by Wong and Sim (2000) to test for goodness of fit. A weighted version of Wong and Sim (2000) under ranked set sampling, a sampling technique introduced by McIntyre (1952), is examined. Simulations that show the ranked set sampling counterpart of Wong and Sim (2000) is more powerful.


Bayesian Analysis Of Location-Scale Family Of Distributions Using S-Plus And R Software, Sheikh Parvaiz Ahmad, Aquil Ahmed, Athar Ali Khan Nov 2010

Bayesian Analysis Of Location-Scale Family Of Distributions Using S-Plus And R Software, Sheikh Parvaiz Ahmad, Aquil Ahmed, Athar Ali Khan

Journal of Modern Applied Statistical Methods

The Normal and Laplace’s methods of approximation for posterior density based on the location-scale family of distributions in terms of the numerical and graphical simulation are examined using S-PLUS and R Software.


Neighbor Balanced Block Designs For Two Factors, Seema Jaggi, Cini Varghese, N. R. Abeynayake Nov 2010

Neighbor Balanced Block Designs For Two Factors, Seema Jaggi, Cini Varghese, N. R. Abeynayake

Journal of Modern Applied Statistical Methods

The concept of Neighbor Balanced Block (NBB) designs is defined for the experimental situation where the treatments are combinations of levels of two factors and only one of the factors exhibits a neighbor effect. Methods of constructing complete NBB designs for two factors in a plot that is strongly neighbor balanced for one factor are obtained. These designs are variance balanced for estimating the direct effects of contrasts pertaining to combinations of levels of both the factors. An incomplete NBB design for two factors is also presented and is found to be partially variance balanced with three associate classes.


Ann Forecasting Models For Ise National-100 Index, Ozer Ozdemir, Atilla Aslanargun, Senay Asma Nov 2010

Ann Forecasting Models For Ise National-100 Index, Ozer Ozdemir, Atilla Aslanargun, Senay Asma

Journal of Modern Applied Statistical Methods

Prediction of the outputs of real world systems with accuracy and high speed is crucial in financial analysis due to its effects on worldwide economics. Because the inputs of the financial systems are timevarying functions, the development of algorithms and methods for modeling such systems cannot be neglected. The most appropriate forecasting model for the ISE national-100 index was investigated. Box- Jenkins autoregressive integrated moving average (ARIMA) and artificial neural networks (ANN) are considered by using several evaluations. Results showed that the ANN model with linear architecture better fits the candidate data.


Bayesian Analysis For Component Manufacturing Processes, L. V. Nandakishore Nov 2010

Bayesian Analysis For Component Manufacturing Processes, L. V. Nandakishore

Journal of Modern Applied Statistical Methods

In manufacturing processes various machines are used to produce the same product. Based on the age, make, etc., of the machines the output may not always follow the same distribution. An attempt is made to introduce Bayesian techniques for a two machine problem. Two cases are presented in this article.


Markov Chain Analysis And Student Academic Progress: An Empirical Comparative Study, Shafiqah Alawadhi, Mokhtar Konsowa Nov 2010

Markov Chain Analysis And Student Academic Progress: An Empirical Comparative Study, Shafiqah Alawadhi, Mokhtar Konsowa

Journal of Modern Applied Statistical Methods

An application of Markov Chain Analysis of student flow at Kuwait University is presented based on a random sample of 1,100 students from the academic years 1996-1997 to 2004-2005. Results were obtained for each college and in total which allows for a comparative study. The students’ mean lifetimes in different levels of study in the colleges as well as the percentage of dropping out of the system are estimated.


On Scientific Research: The Role Of Statistical Modeling And Hypothesis Testing, Lisa L. Harlow Nov 2010

On Scientific Research: The Role Of Statistical Modeling And Hypothesis Testing, Lisa L. Harlow

Journal of Modern Applied Statistical Methods

Comments on Rodgers (2010a, 2010b) and Robinson and Levin (2010) are presented. Rodgers (2010a) initially reported on a growing trend towards more mathematical and statistical modeling; and a move away from null hypothesis significance testing (NHST). He defended and clarified those views in his sequel. Robinson and Levin argued against the perspective espoused by Rodgers and called for more research using experimentally manipulated interventions and less emphasis on correlational research and ill-founded prescriptive statements. In this response, the goal of science and major scientific approaches are discussed as well as their strengths and shortcomings. Consideration is given to how their …