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Applied Statistics

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Articles 421 - 450 of 1191

Full-Text Articles in Statistical Theory

Bayesian Inference For Volatility Of Stock Prices, Juliet G. D'Cunha, K. A. Rao Nov 2014

Bayesian Inference For Volatility Of Stock Prices, Juliet G. D'Cunha, K. A. Rao

Journal of Modern Applied Statistical Methods

Lognormal distribution is widely used in the analysis of failure time data and stock prices. Maximum likelihood and Bayes estimator of the coefficient of variation of lognormal distribution along with confidence/credible intervals are developed. The utility of Bayes procedure is illustrated by analyzing prices of selected stocks.

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Local Bandwidths For Improving Performance Statistics Of Model-Robust Regression 2, Efosa Edionwe, Julian L. Mbegbu Nov 2014

Local Bandwidths For Improving Performance Statistics Of Model-Robust Regression 2, Efosa Edionwe, Julian L. Mbegbu

Journal of Modern Applied Statistical Methods

Model-Robust Regression 2 (MRR2) method is a semi-parametric regression approach that combines parametric and nonparametric fits. The bandwidth controls the smoothness of the nonparametric portion. We present a methodology for deriving data-driven local bandwidth that enhances the performance of MRR2 method for fitting curves to data generated from designed experiments.

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Contrast Of Bayesian And Classical Sample Size Determination, Farhana Sadia, Syed S. Hossain Nov 2014

Contrast Of Bayesian And Classical Sample Size Determination, Farhana Sadia, Syed S. Hossain

Journal of Modern Applied Statistical Methods

Sample size determination is a prerequisite for statistical surveys. A comprehensive overview of the Bayesian approach for computation of the sample size, and a comparison with classical approaches, is presented. Two surveys are taken as example to illustrate the accuracy and efficiency of each approach, and to make recommendations about which method is preferred. The Bayesian approach of sample size determination may require fewer subjects if proper prior information is available.

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The Information Criterion, Masume Ghahramani Nov 2014

The Information Criterion, Masume Ghahramani

Journal of Modern Applied Statistical Methods

The Akaike information criterion, AIC, is widely used for model selection. Using the AIC as the estimator of asymptotic unbias for the second term Kullbake-Leibler risk considers the divergence between the true model and offered models. However, it is an inconsistent estimator. A proposed approach the problem is the use of A'IC, a consistently offered information criterion. Model selection of classic and linear models are considered by a Monte Carlo simulation.

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Gumbel-Weibull Distribution: Properties And Applications, Raid Al-Aqtash, Carl Lee, Felix Famoye Nov 2014

Gumbel-Weibull Distribution: Properties And Applications, Raid Al-Aqtash, Carl Lee, Felix Famoye

Journal of Modern Applied Statistical Methods

Some properties of the Gumbel-Weibull distribution including the mean deviations and modes are studied. A detailed discussion of regions of unimodality and bimodality is given. The method of maximum likelihood is proposed for estimating the distribution parameters and a simulation is conducted to study the performance of the method. Three tests are given for testing the significance of a distribution parameter. The applications of Gumbel-Weibull distribution are emphasized. Five data sets are used to illustrate the flexibility of the distribution in fitting unimodal and bimodal data sets.

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Fitting Stereotype Logistic Regression Models For Ordinal Response Variables In Educational Research (Stata), Xing Liu Nov 2014

Fitting Stereotype Logistic Regression Models For Ordinal Response Variables In Educational Research (Stata), Xing Liu

Journal of Modern Applied Statistical Methods

The stereotype logistic (SL) model is an alternative to the proportional odds (PO) model for ordinal response variables when the proportional odds assumption is violated. This model seems to be underutilized. One major reason is the constraint of current statistical software packages. Statistical Package for the Social Sciences (SPSS) cannot perform the SL regression analysis, and SAS does not have the procedure developed to directly estimate the model. The purpose of this article was to illustrate the stereotype logistic (SL) regression model, and apply it to estimate mathematics proficiency level of high school students using Stata. In addition, it compared …

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Optimal Location Design For Prediction Of Spatial Correlated Environmental Functional Data, Mahdi Rasekhi, B. Jamshidi, F. Rivaz Nov 2014

Optimal Location Design For Prediction Of Spatial Correlated Environmental Functional Data, Mahdi Rasekhi, B. Jamshidi, F. Rivaz

Journal of Modern Applied Statistical Methods

The optimal choice of sites to make spatial prediction is critical for a better understanding of really spatio-temporal data. It is important to obtain the essential spatio-temporal variability of the process in determining optimal design, because these data tend to exhibit both spatial and temporal variability. Two new methods of prediction for spatially correlated functional data are considered. The first method models spatial dependency by fitting variogram to empirical variogram, similar to ordinary kriging (univariate approach). The second method models spatial dependency by linear model co-regionalization (multivariate approach). The variance of prediction method was chosen as the optimization design criterion. …

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Missing Data And The Statistical Modeling Of Adolescent Pregnancy, Dudley L. Poston Dr., Eugenia Conde Dr. Nov 2014

Missing Data And The Statistical Modeling Of Adolescent Pregnancy, Dudley L. Poston Dr., Eugenia Conde Dr.

Journal of Modern Applied Statistical Methods

Missing data is a pervasive problem in social science research. Many techniques have been developed to handle the problem. Different ways of handling missing data were shown to lead to different results in statistical models. A demonstration was given based on statistical modeling of the likelihood of a woman reporting having had an adolescent pregnancy by handling missing data with several different approaches. Results indicate that many of the independent variables in the model vary in whether they are, or are not, statistically significant in predicting the log odds of a woman having a teen pregnancy, and in the ranking …

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Conover’S F Test As An Alternative To Durbin’S Test, Donald J. Best, John Charles Rayner Nov 2014

Conover’S F Test As An Alternative To Durbin’S Test, Donald J. Best, John Charles Rayner

Journal of Modern Applied Statistical Methods

Data consisting of ranks within blocks are considered for balanced incomplete block designs. An F test statistic from ANOVA is better approximated by an F distribution than the Durbin statistic is approximated by a chi-squared distribution. Indicative powers demonstrate that the F test is generally superior to Durbin’s test.

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A Bivariate Distribution With Conditional Gamma And Its Multivariate Form, Sumen Sen, Rajan Lamichhane, Norou Diawara Nov 2014

A Bivariate Distribution With Conditional Gamma And Its Multivariate Form, Sumen Sen, Rajan Lamichhane, Norou Diawara

Journal of Modern Applied Statistical Methods

A bivariate distribution whose marginal are gamma and beta prime distribution is introduced. The distribution is derived and the generation of such bivariate sample is shown. Extension of the results are given in the multivariate case under a joint independent component analysis method. Simulated applications are given and they show consistency of our approach. Estimation procedures for the bivariate case are provided.

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Reliability Estimates Of Generalized Poisson Distribution And Generalized Geometric Series Distribution, Adil H. Khan, T R. Jan Nov 2014

Reliability Estimates Of Generalized Poisson Distribution And Generalized Geometric Series Distribution, Adil H. Khan, T R. Jan

Journal of Modern Applied Statistical Methods

Discrete distributions have played an important role in the reliability theory. In order to obtain Bayes estimators, researchers have adopted various conventional techniques. Generalizing the results of Maiti (1995), Chaturvadi and Tomer (2002) dealt with the problem of estimating P{X1, X2, …, Xk ≤ Y}, where random variables X and Y were assumed to follow a negative binomial distribution. Agit et al. obtained Bayesian estimates of the reliability functions and P{X1, X2, …, Xk ≤ Y} considering X and Y following binomial and Poisson …

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Front Matter, Jmasm Editors Nov 2014

Front Matter, Jmasm Editors

Journal of Modern Applied Statistical Methods

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Improved Randomization Tests For A Class Of Single-Case Intervention Designs, Joel R. Levin, John M. Ferron, Boris S. Gafurov Nov 2014

Improved Randomization Tests For A Class Of Single-Case Intervention Designs, Joel R. Levin, John M. Ferron, Boris S. Gafurov

Journal of Modern Applied Statistical Methods

Forty years ago, Eugene Edgington developed a single-case AB intervention design-and-analysis procedure based on a random determination of the point at which the B phase would start. In the present simulation studies encompassing a variety of AB-type contexts, it is demonstrated that by also randomizing the order in which the A and B phases are administered, a researcher can markedly increase the procedure’s statistical power.

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Robust Winsorized Shrinkage Estimators For Linear Regression Model, Nileshkumar H. Jadhav, D N. Kashid Nov 2014

Robust Winsorized Shrinkage Estimators For Linear Regression Model, Nileshkumar H. Jadhav, D N. Kashid

Journal of Modern Applied Statistical Methods

In multiple linear regression, the ordinary least squares estimator is very sensitive to the presence of multicollinearity and outliers in the response variable. To handle these problems in the data, Winsorized shrinkage estimators are proposed and the performance of these estimators is evaluated through mean square error sense.

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Discrete Generalized Burr-Type Xii Distribution, B. A. Para, T. R. Jan Nov 2014

Discrete Generalized Burr-Type Xii Distribution, B. A. Para, T. R. Jan

Journal of Modern Applied Statistical Methods

A discrete analogue of generalized Burr-type XII distribution is introduced using a general approach of discretizing a continuous distribution. It may be worth exploring the possibility of developing a discrete version of the six parameter generalized Burr-type XII distribution for use in modeling a discrete data. This distribution is suggested as a suitable reliability model to fit a range of discrete lifetime data, as it is shown that hazard rate function can attain monotonic increasing (deceasing) shape for certain values of parameters. The equivalence of discrete generalized Burr-type XII (DGBD-XII) and continuous generalized Burr-type XII (GBD-XII) distributions has been established. …

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Bayesian Estimation Of The Parameters Of Two-Component Mixture Of Rayleigh Distribution Under Doubly Censoring, Tahassum N. Sindhu, Navid Feroze, Muhammad Aslam Nov 2014

Bayesian Estimation Of The Parameters Of Two-Component Mixture Of Rayleigh Distribution Under Doubly Censoring, Tahassum N. Sindhu, Navid Feroze, Muhammad Aslam

Journal of Modern Applied Statistical Methods

Recently, the Bayesian analysis of the two-component mixture of lifetime models under singly type I censored samples was discussed. The Bayes estimation of the parameters of mixture of two Rayleigh distributions (MTRD) is developed under doubly censoring. Different informative priors, under squared error loss function and k-loss function, have been assumed for the posterior estimation. The performance of different estimators has been compared in terms of posterior risks by analyzing the simulated and real life data sets.

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Survival Estimation Using Bootstrap, Jackknife And K-Repeated Jackknife Methods, Johnson A. Adewara, Ugochukwu A. Mbata Nov 2014

Survival Estimation Using Bootstrap, Jackknife And K-Repeated Jackknife Methods, Johnson A. Adewara, Ugochukwu A. Mbata

Journal of Modern Applied Statistical Methods

Three re-sampling techniques are used to estimate the survival probabilities from an exponential life-time distribution. The aim is to employ a technique to obtain a parameter estimate for a two-parameter exponential distribution. The re-sampling methods considered are: Bootstrap estimation method (BE), Jackknife estimation method (JE) and the k-repeated Jackknife estimation method (KJE). The methods were computed to obtain the mean square error (MSE) and mean percentage error (MPE) based on simulated data. The estimates of the two-parameter exponential distribution were substituted to estimate survival probabilities. Results show that the MSE value is reduced when the K–repeated jackknife method …

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Some Methods Of Estimation From Censored Samples In Exponential And Gamma Models, R R. L Kantam, B Sriram Nov 2014

Some Methods Of Estimation From Censored Samples In Exponential And Gamma Models, R R. L Kantam, B Sriram

Journal of Modern Applied Statistical Methods

Two popular life testing models exponential and one where its generalization is gamma are considered. Estimation of scale parameter from a general Type-II doubly censored sample is attempted by the principle of maximum likelihood method. Resulting equations found to be giving iterative solutions. As an alternative to iterative solution certain admissible modifications to the estimating equations are suggested in special cases. The resulting estimates are compared with the exact maximum likelihood estimates analytically or through simulation. The results are also extended for reliability estimation.

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Vol. 13, No. 2 (Full Issue), Jmasm Editors Nov 2014

Vol. 13, No. 2 (Full Issue), Jmasm Editors

Journal of Modern Applied Statistical Methods

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Comparison Of Estimators In Glm With Binary Data, D. M. Sakate, D. N. Kashid Nov 2014

Comparison Of Estimators In Glm With Binary Data, D. M. Sakate, D. N. Kashid

Journal of Modern Applied Statistical Methods

Maximum likelihood estimates (MLE) of regression parameters in the generalized linear models (GLM) are biased and their bias is non negligible when sample size is small. This study focuses on the GLM with binary data with multiple observations on response for each predictor value when sample size is small. The performance of the estimation methods in Cordeiro and McCullagh (1991), Firth (1993) and Pardo et al. (2005) are compared for GLM with binary data using an extensive Monte Carlo simulation study. Performance of these methods for three real data sets is also compared.

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Life Testing Analysis Of Failure Censored Generalized Exponentiated Data, Anwar Hassan, Mehraj Ahmad Nov 2014

Life Testing Analysis Of Failure Censored Generalized Exponentiated Data, Anwar Hassan, Mehraj Ahmad

Journal of Modern Applied Statistical Methods

A generalized exponential distribution is considered for analyzing lifetime data; such statistical models are applicable when the observations are available in an ordered manner. This study examines failure censored data, which consist of testing n items and terminating the experiment when a pre-assigned number of items, for example r ( < n), have failed. Due to scale and shape parameters, both have flexibility for analyzing different types of lifetime data. This distribution has increasing, decreasing and a constant hazard rate depending on the shape parameter. This study provides maximum likelihood estimation and uniformly minimum variance unbiased techniques for the estimation of reliability of a component. Numerical computation was conducted on a data set and a comparison of the performance of two different techniques is presented.

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Ridge Regression And Ill-Conditioning, Ghadban Khalaf, Mohamed Iguernane Nov 2014

Ridge Regression And Ill-Conditioning, Ghadban Khalaf, Mohamed Iguernane

Journal of Modern Applied Statistical Methods

Hoerl and Kennard (1970) suggested the ridge regression estimator as an alternative to the Ordinary Least Squares (OLS) estimator in the presence of multicollinearity. This article proposes new methods for estimating the ridge parameter in case of ordinary ridge regression. A simulation study evaluates the performance of the proposed estimators based on the Mean Squared Error (MSE) criterion and indicates that, under certain conditions, the proposed estimators perform well compared to the OLS estimator and another well-known estimator reviewed.

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Estimation Of Multi Component Systems Reliability In Stress-Strength Models, Adil H. Khan, T R. Jan Nov 2014

Estimation Of Multi Component Systems Reliability In Stress-Strength Models, Adil H. Khan, T R. Jan

Journal of Modern Applied Statistical Methods

In a system with standby redundancy, there are a number of components only one of which works at a time and the other remain as standbys. When an impact of stress exceeds the strength of the active component, for the first time, it fails and another from standbys, if there is any, is activated and faces the impact of stresses, not necessarily identical as faced by the preceding component and the system fails when all the components have failed. Sriwastav and Kakaty (1981) assumed that the components stress-strengths are similarly distributed. However, in general the stress distributions will …

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Estimation Of Gumbel Parameters Under Ranked Set Sampling, Omar M. Yousef, Sameer A. Al-Subh Nov 2014

Estimation Of Gumbel Parameters Under Ranked Set Sampling, Omar M. Yousef, Sameer A. Al-Subh

Journal of Modern Applied Statistical Methods

Consider the MLEs (maximum likelihood estimators) of the parameters of the Gumbel distribution using SRS (simple random sample) and RSS (ranked set sample) and the MOMEs (method of moment estimators) and REGs (regression estimators) based on SRS. A comparison between these estimators using bias and MSE (mean square error) was performed using simulation. It appears that the MLE based on RSS can be a robust competitor to the MLE based on SRS.

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Estimates And Forecasts Of Garch Model Under Misspecified Probability Distributions: A Monte Carlo Simulation Approach, Olaoluwa S. Yaya, Olusanya E. Olubusoye, Oluwadare O. Ojo Nov 2014

Estimates And Forecasts Of Garch Model Under Misspecified Probability Distributions: A Monte Carlo Simulation Approach, Olaoluwa S. Yaya, Olusanya E. Olubusoye, Oluwadare O. Ojo

Journal of Modern Applied Statistical Methods

The effect of misspecification of correct sampling probability distribution of Generalized Autoregressive Conditionally Heteroscedastic (GARCH) processes is considered. The three assumed distributions are the normal, Student t, and generalized error distributions. The GARCH process is sampled using one of the distributions and the model is estimated based on the three distributions in each sample. Parameter estimates and forecast performance are used to judge the estimated model for performance. The AR-GARCH-GED performed better on the three assumed distributions; even, when Student t distribution is assumed, AR-GARCH-Student t does not perform as the best model.

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End Matter, Jmasm Editors Nov 2014

End Matter, Jmasm Editors

Journal of Modern Applied Statistical Methods

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Double Bootstrap Confidence Interval Estimates With Censored And Truncated Data, Jayanthi Arasan, Mohd B. Adam Nov 2014

Double Bootstrap Confidence Interval Estimates With Censored And Truncated Data, Jayanthi Arasan, Mohd B. Adam

Journal of Modern Applied Statistical Methods

Traditional inferential procedures often fail with censored and truncated data, especially when sample sizes are small. In this paper we evaluate the performances of the double and single bootstrap interval estimates by comparing the double percentile (DB-p), double percentile-t (DB-t), single percentile (B-p), and percentile-t (B-t) bootstrap interval estimation methods via a coverage probability study when the data is censored using the log logistic model. We then apply the double bootstrap intervals to real right censored lifetime data on 32 women with breast cancer and failure data on 98 brake pads where all the observations were left truncated.

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Bias And Precision Of The Squared Canonical Correlation Coefficient Under Nonnormal Data Condition, Lesley F. Leach, Robin K. Henson May 2014

Bias And Precision Of The Squared Canonical Correlation Coefficient Under Nonnormal Data Condition, Lesley F. Leach, Robin K. Henson

Journal of Modern Applied Statistical Methods

Monte Carlo methods were employed to investigate the effect of nonnormality on the bias associated with the squared canonical correlation coefficient (Rc2). The majority of Rc2 estimates were found to be extremely biased, but the magnitude of bias was impacted little by the degree of nonnormality.

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Stochastic Randomized Response Model For A Quantitative Sensitive Random Variable, Sarjinder Singh, Stephen A. Sedory May 2014

Stochastic Randomized Response Model For A Quantitative Sensitive Random Variable, Sarjinder Singh, Stephen A. Sedory

Journal of Modern Applied Statistical Methods

A new stochastic randomized response model is introduced that is useful for estimating the population mean of a sensitive quantitative variable. The proposed stochastic randomized response model is an extension of the stochastic randomized response model from a qualitative sensitive variable to a quantitative variable found in Singh (2002). The stochastic nature of a randomized response device helps increase a respondent’s cooperation while collecting information on sensitive variables in a society. The Bar-Lev, Bobovitch, and Boukai (2004) model is shown to be a special case of the proposed model.

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Ridge Regression In Calibration Models With Symmetric Padding Extension-Daubechies Wavelet Transform Preprocessing, Nurwiani, S Sunaryo, Setiawan, B W. Otok May 2014

Ridge Regression In Calibration Models With Symmetric Padding Extension-Daubechies Wavelet Transform Preprocessing, Nurwiani, S Sunaryo, Setiawan, B W. Otok

Journal of Modern Applied Statistical Methods

Wavelet transformation is commonly used in calibration models as a preprocessing step. This preprocessing does not involve all results of a spectrum discretization; consequently, a lot of information can be missing. To avoid missing information, a symmetric padding extension (SPE) can be used to place all data points into dyadic scales, however, high dimensional discretization points need to be reduced. Dimension reduction can be performed with Daubechies wavelet transformation (DWT). Scale function and Daubechies wavelet are continuous functions, thus they perform a faster approximation. SPE-DWT preprocessing combines SPE and DWT. Multicollinearity often occurs in calibration models; the ridge regression (RR) …

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