Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Applied Statistics (66)
- Social and Behavioral Sciences (65)
- Statistical Methodology (14)
- Statistical Models (11)
- Design of Experiments and Sample Surveys (9)
-
- Other Statistics and Probability (9)
- Survival Analysis (9)
- Agricultural and Resource Economics (8)
- Artificial Intelligence and Robotics (8)
- Behavioral Economics (8)
- Business (8)
- Categorical Data Analysis (8)
- Computer Sciences (8)
- Data Science (8)
- Databases and Information Systems (8)
- Development Studies (8)
- Econometrics (8)
- Economic Theory (8)
- Economics (8)
- Finance (8)
- Food Security (8)
- Growth and Development (8)
- Income Distribution (8)
- Longitudinal Data Analysis and Time Series (8)
- Macroeconomics (8)
- Multivariate Analysis (8)
- Numerical Analysis and Scientific Computing (8)
- Institution
- Keyword
-
- Statistics (5)
- Exchangeability (4)
- Non-parametric (4)
- Null hypothesis (4)
- Permutation test (4)
-
- Type I error (4)
- Validity (4)
- Clustering (3)
- Mean squared error (3)
- Monte Carlo simulation (3)
- P-value (3)
- Bias (2)
- Bootstrap (2)
- Confidence interval (2)
- Control charts (2)
- Data mining (2)
- Discrete set (2)
- Maximum likelihood estimation (2)
- Robustness (2)
- Significance level (2)
- Stata (2)
- Vine (2)
- ANOVA (1)
- Akaike Information Criterion (1)
- All Share Index (1)
- Area under the curve (1)
- Assessing normality (1)
- Asthma mortality (1)
- Asymptotic linearity (1)
- Autoregressive Process (1)
- Publication
- Publication Type
Articles 1 - 30 of 77
Full-Text Articles in Statistical Theory
Simulating Bipartite Networks To Reflect Uncertainty In Local Network Properties, Ravi Goyal, Joseph Blitzstein, Victor De Gruttola
Simulating Bipartite Networks To Reflect Uncertainty In Local Network Properties, Ravi Goyal, Joseph Blitzstein, Victor De Gruttola
Harvard University Biostatistics Working Paper Series
No abstract provided.
Short-Term Inflation Forecasting Models For Nigeria, Sani I. Doguwa, Sarah O. Alade
Short-Term Inflation Forecasting Models For Nigeria, Sani I. Doguwa, Sarah O. Alade
CBN Journal of Applied Statistics (JAS)
Short-term inflation forecasting is an essential component of the monetary policy projections at the Central Bank of Nigeria. This paper proposes four short-term headline inflation forecasting models using the SARIMA and SARIMAX processes and compares their performance using the pseudo-out-of-sample forecasting procedure over July 2011 to September 2013. According to the results the best forecasting performance is demonstrated by the model based on the all items CPI estimated using the SARIMAX model. This model is, therefore, recommended for use in short-term forecasting of headline inflation in Nigeria. The forecasting performance up to eight months ahead, of the models based on …
An Efficient Two Sample Capture-Recapture Model With High Recaptures, Danjuma Jibasen, Yusuf J. Adams
An Efficient Two Sample Capture-Recapture Model With High Recaptures, Danjuma Jibasen, Yusuf J. Adams
CBN Journal of Applied Statistics (JAS)
This paper proposed an efficient two sample capture-recapture model (Ma) with high recaptures and compared it with the existing models like the model of no factor effect (Mo), behavioral response model (Mb) and the Petersen model (Ms), using simulated data. We found that the Petersen model provides a better estimate of the population size when the observations follow a hypergeometric distribution and the population is overestimated when recapture is high. It was also found that the proposed model provides a better estimator of the population size than the existing ones when the recapture is high. This model is particularly useful …
Causal Relationship Between Stock Market Index And Exchange Rate: Evidence From Nigeria, Abdulrasheed Zubair
Causal Relationship Between Stock Market Index And Exchange Rate: Evidence From Nigeria, Abdulrasheed Zubair
CBN Journal of Applied Statistics (JAS)
This paper uses Johansen’s cointegration to test for the possibility of cointegration and Granger-causality to estimate the causal relationship between stock market index and monetary indicators (exchange rate and M2) before and during the global financial crisis for Nigeria, using monthly data for the period 2001–2011. Results suggest absence of long-run relationship before and during the crisis. The Granger-causality tests show a uni-directional causality running from M2 to ASI before the crisis while during the period of the crisis there is absence of causality between the variables. This suggests that ASI show responsiveness to M2. Thus, absence of the direct …
Investigating Chaos In The Nigerian Asset And Resource Management (Arm) Discovery Fund, Ibiyinka A. Fuwape, Samuel T. Ogunjo
Investigating Chaos In The Nigerian Asset And Resource Management (Arm) Discovery Fund, Ibiyinka A. Fuwape, Samuel T. Ogunjo
CBN Journal of Applied Statistics (JAS)
This paper investigates chaos in a Nigerian mutual fund, Asset and Resource Management Company Limited (ARM) for a period of eleven years. The existence of chaotic signals in the data was identified by the reconstruction of the phase space of the daily closing price of the fund and the delay time was quantified using mutual information function and the embedding dimension by the false nearest neighbours, where the values were identified to be 15 and 20 respectively. The presence of chaotic signals in the ARM data was further confirmed by the correlation dimension method which yielded a dimension of 2.2 …
Modeling The Nigerian Inflation Rates Using Periodogram And Fourier Series Analysis, Chukwuemeka O. Omekara,, Emmanuel J. Ekpenyong, Micheal P. Ekerete
Modeling The Nigerian Inflation Rates Using Periodogram And Fourier Series Analysis, Chukwuemeka O. Omekara,, Emmanuel J. Ekpenyong, Micheal P. Ekerete
CBN Journal of Applied Statistics (JAS)
This work considers the application of Periodogram and Fourier Series Analysis to model all-items monthly inflation rates in Nigeria from 2003 to 2011. The main objectives are to identify inflation cycles, fit a suitable model to the data and make forecasts of future values. To achieve these objectives, monthly all-items inflation rates for the period were obtained from the Central Bank of Nigeria (CBN) website. Periodogram and Fourier series methods of analysis are used to analyze the data. Based on the analysis, it was found that inflation cycle within the period was fifty one (51) months, which coincides with the …
Nigerian Stock Index: A Search For Optimal Garch Model Using High Frequency Data, Olaoluwa Simon Yaya
Nigerian Stock Index: A Search For Optimal Garch Model Using High Frequency Data, Olaoluwa Simon Yaya
CBN Journal of Applied Statistics (JAS)
This paper attempts to fit the best Generalized Autoregressive Conditional Heteroscedastic (GARCH) model for All Share Index (ASI) of Nigerian Stock Exchange (NSE) returns. A search is made on various GARCH variants specified on the assumptions of stationarity and asymmetry. Fractionally integrated types are also considered to capture the possibility of return series having property of long range dependency. The parameter estimations are carried out on the assumptions of normality and non-normality of GARCH innovations, with models and forecasts evaluated using information criteria and loss functions respectively. Under normality assumption, Hyperbolic GARCH (HYGARCH(1,d,1)) model is selected and Integrated GARCH (IGARCH(1,1)) …
Time Series Modeling Of Nigeria External Reserves, Iheanyichukwu S. Iwueze, Eleazar C. Nwogu, Valentine U. Nlebedim
Time Series Modeling Of Nigeria External Reserves, Iheanyichukwu S. Iwueze, Eleazar C. Nwogu, Valentine U. Nlebedim
CBN Journal of Applied Statistics (JAS)
This paper discusses the levels and trend of external reserves in Nigeria. The relevance of this lies in the fact that it could help to monitor the reserves and throw early warning signal about any economic crisis. Monthly data on Nigeria external reserves for the period January 1999 to December, 2008 derived from the 2008 CBN Statistical Bulletin was analyzed using ARIMA model. Results of the analyses show that (i) the data requires logarithmic transformation to stabilize the variance and make the distribution normal (ii) the appropriate model that best describes the pattern in the transformed data is the Autoregressive- …
A Markov Decision Process Approach To Optimal Control Of A Multi-Level Hierarchical Manpower System, Akaninyene U. Udom
A Markov Decision Process Approach To Optimal Control Of A Multi-Level Hierarchical Manpower System, Akaninyene U. Udom
CBN Journal of Applied Statistics (JAS)
A recurrent problem in manpower control is how to attain the desired structural configuration in an optimal way, since it is possible to reach a desired structural configuration using different control inputs. The major aim of this paper is to develop a Markov Decision Process for optimal control of a Multi-level Hierarchical Manpower System (MHMS) by promotion and interdepartmental transfers. This is examined under control by intervention and contraction cost Markov Decision Process.
A Monte Carlo Comparison Of Robust Manova Test Statistics, Holmes Finch, Brian French
A Monte Carlo Comparison Of Robust Manova Test Statistics, Holmes Finch, Brian French
Journal of Modern Applied Statistical Methods
Multivariate Analysis of Variance (MANOVA) is a popular statistical tool in the social sciences, allowing for the comparison of mean vectors across groups. MANOVA rests on three primary assumptions regarding the population: (a) multivariate normality, (b) equality of group population covariance matrices and (c) independence of errors. When these assumptions are violated, MANOVA does not perform well with respect to Type I error and power. There are several alternative test statistics that can be considered including robust statistics and the use of the structural equation modeling (SEM) framework. This simulation study focused on comparing the performance of the P test …
On Some Properties Of A Heterogeneous Transfer Function Involving Symmetric Saturated Linear (Satlins) With Hyperbolic Tangent (Tanh) Transfer Functions, Christopher Godwin Udomboso
On Some Properties Of A Heterogeneous Transfer Function Involving Symmetric Saturated Linear (Satlins) With Hyperbolic Tangent (Tanh) Transfer Functions, Christopher Godwin Udomboso
Journal of Modern Applied Statistical Methods
For transfer functions to map the input layer of the statistical neural network model to the output layer perfectly, they must lie within bounds that characterize probability distributions. The heterogeneous transfer function, SATLINS_TANH, is established as a Probability Distribution Function (p.d.f), and its mean and variance are shown.
Distribution Of The Ratio Of Normal And Rice Random Variables, Nayereh B. Khoolenjani, Kavoos Khorshidian
Distribution Of The Ratio Of Normal And Rice Random Variables, Nayereh B. Khoolenjani, Kavoos Khorshidian
Journal of Modern Applied Statistical Methods
The ratio of independent random variables arises in many applied problems. The distribution of the ratio |X/Y| is studied when X and Y are independent Normal and Rice random variables, respectively. Ratios of such random variables have extensive applications in the analysis of noises in communication systems. The exact forms of probability density function (PDF), cumulative distribution function (CDF) and the existing moments are derived in terms of several special functions. As a special case, the PDF and CDF of the ratio of independent standard Normal and Rayleigh random variables have been obtained. Tabulations of associated percentage points …
Front Matter, Jmasm Editors
Front Matter, Jmasm Editors
Journal of Modern Applied Statistical Methods
No abstract provided.
Preliminary Testing For Normality: Is This A Good Practice?, H. J. Keselman, Abdul R. Othman, Rand R. Wilcox
Preliminary Testing For Normality: Is This A Good Practice?, H. J. Keselman, Abdul R. Othman, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
Normality is a distributional requirement of classical test statistics. In order for the test statistic to provide valid results leading to sound and reliable conclusions this requirement must be satisfied. In the not too distant past, it was claimed that violations of normality would not likely jeopardize scientific findings (See Hsu & Feldt, 1969; Lunney, 1970). Recent revelations suggest otherwise (See e.g., Micceri, 1989; Keselman, Huberty, Lix et al., 1998; Erceg-Hurn, Wilcox, & Keselman, 2013; Wilcox and Keselman, 2003; Wilcox, 2012a, b). Unfortunately the data obtained in psychological investigations rarely, if ever, meet the requirement of normally distributed data (Micceri, …
Intrinsically Ties Adjusted Non-Parametric Method For The Analysis Of Two Sampled Data, G. U. Ebuh, I. C. A Oyeka
Intrinsically Ties Adjusted Non-Parametric Method For The Analysis Of Two Sampled Data, G. U. Ebuh, I. C. A Oyeka
Journal of Modern Applied Statistical Methods
A non-parametric method for the analysis of two sample data is proposed that intrinsically and structurally adjusts the test statistic for the possible presence of tied observations between the sampled populations, thereby obviating the need to require the populations to be continuous. The populations may be measurements on as low as the ordinal scale, and need not be homogeneous. In cases where the null hypotheses are rejected, the test statistic enables the determination of which of the sampled populations is likely to be responsible for the rejection (a determination which the Wilcoxon Mann Whitney test cannot handle). The proposed method …
The Impact Of Continuity Violation On Anova And Alternative Methods, Björn Lantz
The Impact Of Continuity Violation On Anova And Alternative Methods, Björn Lantz
Journal of Modern Applied Statistical Methods
The normality assumption behind ANOVA and other parametric methods implies that response variables are measured on continuous scales. A simulation approach is used to explore the impact of continuity violation on the performance of statistical methods commonly used by applied researchers to compare locations across several groups.
The Single-Case Data Analysis Package: Analysing Single-Case Experiments With R Software, Isis Bulté, Patrick Onghena
The Single-Case Data Analysis Package: Analysing Single-Case Experiments With R Software, Isis Bulté, Patrick Onghena
Journal of Modern Applied Statistical Methods
The RcmdrPlugin.SCDA plug-in package is discussed. It integrates three R packages in the R commander interface: SCVA (for Single-Case Visual Analysis), SCRT (for Single-Case Randomization Tests), and SCMA (for Single-Case Meta-Analysis). This way the plug-in package covers three important steps in the analysis of single-case data.
A Comparison Between Biased And Unbiased Estimators In Ordinary Least Squares Regression, Ghadban Khalaf
A Comparison Between Biased And Unbiased Estimators In Ordinary Least Squares Regression, Ghadban Khalaf
Journal of Modern Applied Statistical Methods
During the past years, different kinds of estimators have been proposed as alternatives to the Ordinary Least Squares (OLS) estimator for the estimation of the regression coefficients in the presence of multicollinearity. In the general linear regression model, Y = Xβ + e, it is known that multicollinearity makes statistical inference difficult and may even seriously distort the inference. Ridge regression, as viewed here, defines a class of estimators of β indexed by a scalar parameter k. Two methods of specifying k are proposed and evaluated in terms of Mean Square Error (MSE) by …
Discriminating Between Generalized Exponential Distribution And Some Life Test Models Based On Population Quantiles, B. Srinivasa Rao, R. R. L Kantam
Discriminating Between Generalized Exponential Distribution And Some Life Test Models Based On Population Quantiles, B. Srinivasa Rao, R. R. L Kantam
Journal of Modern Applied Statistical Methods
A test statistic based on population quantiles using sample order statistics is suggested. The quantiles of the test statistics are evaluated for generalized exponential distribution. Similar test statistic based on moments of sample order statistic is referred and the proposed test formula is compared with it. Between the pairs of the above models it is established that the test formula proposed by us is more effective and useful than the formula based on the moments of order statistics as developed by Sultan (2007).
Comparison Of Parameters Of Lognormal Distribution Based On The Classical And Posterior Estimates, Raja Sultan, S. P. Ahmad
Comparison Of Parameters Of Lognormal Distribution Based On The Classical And Posterior Estimates, Raja Sultan, S. P. Ahmad
Journal of Modern Applied Statistical Methods
Lognormal distribution is widely used in scientific field, such as agricultural, entomological, biology etc. If a variable can be thought as the multiplicative product of some positive independent random variables, then it could be modelled as lognormal. In this study, maximum likelihood estimates and posterior estimates of the parameters of lognormal distribution are obtained and using these estimates we calculate the point estimates of mean and variance for making comparisons.
On Bayesian Estimation And Predictions For Two-Component Mixture Of The Gompertz Distribution, Navid Feroze, Muhammad Aslam
On Bayesian Estimation And Predictions For Two-Component Mixture Of The Gompertz Distribution, Navid Feroze, Muhammad Aslam
Journal of Modern Applied Statistical Methods
Mixtures models have received sizeable attention from analysts in the recent years. Some work on Bayesian estimation of the parameters of mixture models have appeared. However, the were restricted to the Bayes point estimation The methodology for the Bayesian interval estimation of the parameters for said models is still to be explored. This paper proposes the posterior interval estimation (along with point estimation) for the parameters of a two-component mixture of the Gompertz distribution. The posterior predictive intervals are also derived and evaluated. Different informative and non-informative priors are assumed under a couple of loss functions for the posterior analysis. …
A Generalized Class Of Estimators For Finite Population Variance In Presence Of Measurement Errors, Prayas Sharma, Rajesh Singh
A Generalized Class Of Estimators For Finite Population Variance In Presence Of Measurement Errors, Prayas Sharma, Rajesh Singh
Journal of Modern Applied Statistical Methods
The problem of estimating the population variance is presented using auxiliary information in the presence of measurement errors. The estimators in this article use auxiliary information to improve efficiency and assume that measurement error is present both in study and auxiliary variable. A numerical study is carried out to compare the performance of the proposed estimator with other estimators and the variance per unit estimator in the presence of measurement errors.
Robust Regression Estimators When There Are Tied Values, Rand R. Wilcox, Florence Clark
Robust Regression Estimators When There Are Tied Values, Rand R. Wilcox, Florence Clark
Journal of Modern Applied Statistical Methods
It is well known that when using the ordinary least squares regression estimator, outliers among the dependent variable can result in relatively poor power. Many robust regression estimators have been derived that address this problem, but the bulk of the results assume that the dependent variable is continuous. It is demonstrated that when there are tied values, several robust regression estimators can perform poorly in terms of controlling the Type I error probability, even with a large sample size. The presence of tied values does not necessarily mean that they perform poorly, but there is the issue of whether there …
Testing The Assumption Of Non-Differential Misclassification In Case-Control Studies, Tze-San Lee, Qin Hui
Testing The Assumption Of Non-Differential Misclassification In Case-Control Studies, Tze-San Lee, Qin Hui
Journal of Modern Applied Statistical Methods
One of the not yet solved issues regarding the misclassification in case-control studies is whether the misclassification rates are the same for both cases and controls. Currently, a common practice is to assume that the rates are the same, that is, the non-differential misclassification assumption. However, it has been suspected that this assumption may not be valid in practical applications. Unfortunately, no test is available so far to test the validity of the non-differential misclassification assumption. A method is presented to test the validity of non-differential misclassification assumption in case-control studies with 2 × 2 tables when validation data are …
Ordered Logit Regression Modeling Of The Self-Rated Health In Hawai‘I, With Comparisons To The Ols Model, Hosik Min
Journal of Modern Applied Statistical Methods
Despite the ordinal nature of Self-Rated Health (SRH) variable, logistic regression models or regression models have been used without adequate justification for these applications. It is shown that ordered-logit regression model is the appropriate statistical strategy to estimate SRH, whereas the Ordinary LeastSquares model leads to biased conclusions.
Approximation Multivariate Distribution Of Main Indices Of Tehran Stock Exchange With Pair-Copula, G. Parham, A. Daneshkhah, O. Chatrabgoun
Approximation Multivariate Distribution Of Main Indices Of Tehran Stock Exchange With Pair-Copula, G. Parham, A. Daneshkhah, O. Chatrabgoun
Journal of Modern Applied Statistical Methods
The multivariate distribution of five main indices of Tehran stock exchange is approximated using a pair-copula model. A vine graphical model is used to produce an n-dimensional copula. This is accomplished using a flexible copula called a minimum information (MI) copula as a part of pair-copula construction. Obtained results show that the achieved model has a good level of approximation.
Generalized Modified Ratio Estimator For Estimation Of Finite Population Mean, Jambulingam Subramani
Generalized Modified Ratio Estimator For Estimation Of Finite Population Mean, Jambulingam Subramani
Journal of Modern Applied Statistical Methods
A generalized modified ratio estimator is proposed for estimating the population mean using the known population parameters. It is shown that the simple random sampling without replacement sample mean, the usual ratio estimator, the linear regression estimator and all the existing modified ratio estimators are the particular cases of the proposed estimator. The bias and the mean squared error of the proposed estimator are derived and are compared with that of existing estimators. The conditions for which the proposed estimator performs better than the existing estimators are also derived. The performance of the proposed estimator is assessed with that of …
Test For Intraclass Correlation Coefficient Under Unequal Family Sizes, Madhusudan Bhandary, Koji Fujiwara
Test For Intraclass Correlation Coefficient Under Unequal Family Sizes, Madhusudan Bhandary, Koji Fujiwara
Journal of Modern Applied Statistical Methods
Three tests are proposed based on F-distribution, Likelihood Ratio Test (LRT) and large sample Z-test for intraclass correlation coefficient under unequal family sizes based on a single multinormal sample. It has been found that the test based on F-distribution consistently and reliably produces results superior to those of Likelihood Ratio Test (LRT) and large sample Z-test in terms of size for various combinations of intraclass correlation coefficient values. The power of this test based on F-distribution is competitive with the power of the LRT and the power of Z-test is slightly better than the powers of F-test and LRT when …
Variables Sampling Plan For Correlated Data, J. R. Singh, R. Sankle, M. Ahmad Khanday
Variables Sampling Plan For Correlated Data, J. R. Singh, R. Sankle, M. Ahmad Khanday
Journal of Modern Applied Statistical Methods
The sampling plan for the mean for correlated data is studied. The Operating Characteristic (OC) of the variable sampling plan for mean for correlated data are calculated and compared with the OC of known σ case.
Case-Control Studies With Jointly Misclassified Exposure And Confounding Variables, Tze-San Lee
Case-Control Studies With Jointly Misclassified Exposure And Confounding Variables, Tze-San Lee
Journal of Modern Applied Statistical Methods
The issue of 2 × 2 × 2 case-control studies is addressed when both exposure and confounding variables are jointly misclassified. Two scenarios are considered: the classification errors of exposure and confounding variables are independent or not independent. The bias-adjusted cell probability estimates which account for the misclassification bias are presented. The effect of misclassification on the measure of crude odds ratio either unstratified or stratified by the confounder, Mantel-Haenszel summary odds ratio, the confounding component in the crude odds ratio, the first and second order multiplicative interaction are assessed through the sensitivity analysis from using the data on the …