Improved Randomization Tests For A Class Of Single-Case Intervention Designs,
2014
University of Arizona
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.
Robust Winsorized Shrinkage Estimators For Linear Regression Model,
2014
D.R.K. College of Commerce, Kolhapur, India
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.
Discrete Generalized Burr-Type Xii Distribution,
2014
University of Kashmir, Srinagar, India
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. …
Bayesian Estimation Of The Parameters Of Two-Component Mixture Of Rayleigh Distribution Under Doubly Censoring,
2014
Quaid-i-Azam University, Islamabad, Pakistan
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.
Survival Estimation Using Bootstrap, Jackknife And K-Repeated Jackknife Methods,
2014
University of Lagos, Akoka-Lagos, Nigeria
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 …
Some Methods Of Estimation From Censored Samples In Exponential And Gamma Models,
2014
Acharya Nagarjuna University, Guntur, India
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.
Vol. 13, No. 2 (Full Issue),
2014
Wayne State University
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,
2014
Shivaji University, Kolhapur, India
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.
Life Testing Analysis Of Failure Censored Generalized Exponentiated Data,
2014
King Saud University, Riyadh, Saudi Arabia
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.
Ridge Regression And Ill-Conditioning,
2014
King Khalid University, Saudi Arabia
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.
Estimation Of Multi Component Systems Reliability In Stress-Strength Models,
2014
University of Kashmir, Srinagar, India
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 …
Estimation Of Gumbel Parameters Under Ranked Set Sampling,
2014
Al Balqa' Applied University, Zarqa, Jordan
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.
Estimates And Forecasts Of Garch Model Under Misspecified Probability Distributions: A Monte Carlo Simulation Approach,
2014
University of Ibadan, Ibadan, Nigeria
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.
End Matter,
2014
Wayne State University
Double Bootstrap Confidence Interval Estimates With Censored And Truncated Data,
2014
University Putra Malaysia, Serdang, Selangor, Malaysia
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.
Exonest: Bayesian Model Selection Applied To The Detection And Characterization Of Exoplanets Via Photometric Variations,
2014
University at Albany, State University of New York
Exonest: Bayesian Model Selection Applied To The Detection And Characterization Of Exoplanets Via Photometric Variations, Ben Placek, Kevin H. Knuth, Daniel Angerhausen
Physics Faculty Scholarship
EXONEST is an algorithm dedicated to detecting and characterizing the photometric signatures of exoplanets, which include reflection and thermal emission, Doppler boosting, and ellipsoidal variations. Using Bayesian inference, we can test between competing models that describe the data as well as estimate model parameters. We demonstrate this approach by testing circular versus eccentric planetary orbital models, as well as testing for the presence or absence of four photometric effects. In addition to using Bayesian model selection, a unique aspect of EXONEST is the potential capability to distinguish between reflective and thermal contributions to the light curve. A case study is …
Stratified Meta-Analysis To Examine Data Biases In Lung Cancer Studies Of Refinery Workers,
2014
Yale University
Stratified Meta-Analysis To Examine Data Biases In Lung Cancer Studies Of Refinery Workers, Sherman Selix
Yale Day of Data
Petroleum refineries employ a variety of workers who historically experienced different potentials for asbestos exposure depending on job tasks. Associations between petroleum refinery work and lung cancer related to occupational asbestos exposure have been quantified among various locations, corporations, and time periods. To combine the data from several individual refinery studies and examine an overall effect, a systematic review and stratified meta-analysis was employed. Using set search terms among four databases, 112 potential publications were identified, of which 29 qualified for meta-analysis. Risk estimates and confidence intervals were extracted from these publications to construct four separate datasets. Inverse variance weighting …
Spatiotemporal Crime Analysis,
2014
Purdue University
Spatiotemporal Crime Analysis, James Q. Tay, Abish Malik, Sherry Towers, David Ebert
The Summer Undergraduate Research Fellowship (SURF) Symposium
There has been a rise in the use of visual analytic techniques to create interactive predictive environments in a range of different applications. These tools help the user sift through massive amounts of data, presenting most useful results in a visual context and enabling the person to rapidly form proactive strategies. In this paper, we present one such visual analytic environment that uses historical crime data to predict future occurrences of crimes, both geographically and temporally. Due to the complexity of this analysis, it is necessary to find an appropriate statistical method for correlative analysis of spatiotemporal data, as well …
Using Remote Sensing Data To Predict The Spread Of Mosquito Borne Disease,
2014
NASA Jet Propulsion Lab
Using Remote Sensing Data To Predict The Spread Of Mosquito Borne Disease, Mary Ellen O'Donnell, Erika Podest
STAR Program Research Presentations
There is interest in how environmental variables derived from satellite data such as temperature, vegetation cover, and precipitation correlate to vector borne disease occurrence such as malaria and dengue fever. This study will be carried out using a decision tree based open source software called Random Forests to find correlations between the remote sensing variables and mosquito abundance. Software will be written in C# to take large amounts of data from the NASA satellite database and automatically format it for the Random Forest Software input. Correlations found, using Random Forests, between disease incidence and the variables can be used as …
The Path To The Sea: Leatherback Hatchling Orientation At Sandy Point National Wildlife Refuge,
2014
JLS Middle School
The Path To The Sea: Leatherback Hatchling Orientation At Sandy Point National Wildlife Refuge, Christina Macmillan, Kelly Stewart
STAR Program Research Presentations
Once sea turtle hatchlings emerge from their nest, they must find their way to the ocean by using cues such as a bright horizon and the slope of the beach. While moving toward the water, hatchlings often must navigate past predators and through vegetation, sticks, footprints in the sand, and other dangers such as ghost crab holes. Sometimes hatchlings become confused (or disoriented) and turn in circles to find the right route to the water. Sea turtle hatchlings also may become disoriented as a result of human impacts such as town lights or trash. The purpose of our experiment was …
