Statistics and Probability Commons^™

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, 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, 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, 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, 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

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.

Remarks On Characterizations Of Malinowska And Szynal, Gholamhossein Hamedani, Z. Javanshiri, Mehdi Maadooliat, A. Yazdani

Mathematics, Statistics and Computer Science Faculty Research and Publications

The problem of characterizing a distribution is an important problem which has recently attracted the attention of many researchers. Thus, various characterizations have been established in many different directions. An investigator will be vitally interested to know if their model fits the requirements of a particular distribution. To this end, one will depend on the characterizations of this distribution which provide conditions under which the underlying distribution is indeed that particular distribution. In this work, several characterizations of Malinowska and Szynal (2008) for certain general classes of distributions are revisited and simpler proofs of them are presented. These characterizations are …

Quantification Of The Statistical Effects Of Spatiotemporal Processing Of Nontask Fmri Data, M. Muge Karaman, Andrew S. Nencka, Iain P. Bruce, Daniel B. Rowe

Mathematics, Statistics and Computer Science Faculty Research and Publications

Nontask functional magnetic resonance imaging (fMRI) has become one of the most popular noninvasive areas of brain mapping research for neuroscientists. In nontask fMRI, various sources of “noise” corrupt the measured blood oxygenation level-dependent signal. Many studies have aimed to attenuate the noise in reconstructed voxel measurements through spatial and temporal processing operations. While these solutions make the data more “appealing,” many commonly used processing operations induce artificial correlations in the acquired data. As such, it becomes increasingly more difficult to derive the true underlying covariance structure once the data have been processed. As the goal of nontask fMRI studies …

Enhanced Precision In The Analysis Of Randomized Trials With Ordinal Outcomes, Iván Díaz, Elizabeth Colantuoni, Michael Rosenblum

Johns Hopkins University, Dept. of Biostatistics Working Papers

We present a general method for estimating the effect of a treatment on an ordinal outcome in randomized trials. The method is robust in that it does not rely on the proportional odds assumption. Our estimator leverages information in prognostic baseline variables, and has all of the following properties: (i) it is consistent; (ii) it is locally efficient; (iii) it is guaranteed to match or improve the precision of the standard, unadjusted estimator. To the best of our knowledge, this is the first estimator of the causal relation between a treatment and an ordinal outcome to satisfy these properties. We …

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 …

Applications Of The Wei-Lachin Multivariate One-Sided Test For Multiple Outcomes On Possibly Different Scales, John M. Lachin

GW Biostatistics Center

Many studies aim to assess whether a therapy has a beneficial effect on multiple outcomes simultaneously relative to a control. Often the joint null hypothesis of no difference for the set of outcomes is tested using separate tests with a correction for multiple tests, or using a multivariate T2-like MANOVA or global test. However, a more powerful test in this case is a multivariate one-sided or one-directional test directed at detecting a simultaneous beneficial treatment effect on each outcome, though not necessarily of the same magnitude. The Wei-Lachin test is a simple 1 df test obtained from a simple …

Boresight Alignment Station, Marco A. Scussat, Richard M. Goeden, Jeffrey S. Scott, Richard G. Lane, Gary B. Hughes

Statistics

A boresight alignment system facilitates aligning a plurality of cameras and/or images of the cameras with respect to one another. The system may have a mount configured to facilitate attachment of a bezel containing a plurality of cameras to the mount. The system may have a plurality of targets and each target may be configured to provide light of at least two different wavelengths and/or ranges of wavelengths. One or more baffles may be disposed optically between the mount and the target assembly to inhibit stray light from being incident upon the cameras.

Optimal Bayesian Adaptive Trials When Treatment Efficacy Depends On Biomarkers, Yifan Zhang, Lorenzo Trippa, Giovanni Parmigiani

Harvard University Biostatistics Working Paper Series

No abstract provided.

Hiv Testing Implementation In Two Urban Cities: Practice, Policy And Perceived Barriers, Camden J. Hallmark, Jennifer Skillicorn, Thomas P. Giordano, Jessica A. Davila, Marlene Mcneese, Nestor Rocha, Avemaria Smith, Stacey Cooper, Amanda D. Castel

Epidemiology Faculty Publications

Background

Although funding has supported the scale up of routine, opt-out HIV testing in the US, variance in implementation mechanisms and barriers in high-burden jurisdictions remains unknown.

Methods

We conducted a survey of health care organizations in Washington, DC and Houston/Harris County to determine number of HIV tests completed in 2011, policy and practices associated with HIV testing, funding mechanisms, and reported barriers to testing in each jurisdiction and to compare results between jurisdictions.

Results

In 2012, 43 Houston and 35 DC HIV-testing organizations participated in the survey. Participants represented 85% of Department of Health-supported testers in DC and 90% …

The Antisymmetry Betweenness Axiom And Hausdorff Continua, Paul Bankston

Mathematics, Statistics and Computer Science Faculty Research and Publications

An interpretation of betweenness on a set satisfies the antisymmetry axiom at a point a if it is impossible for each of two distinct points to lie between the other and a. In this paper we study the role of antisymmetry as it applies to the K-interpretation of betweenness in a Hausdorff continuum X, where a point c lies between points a and b exactly when every subcontinuum of X containing both a and b contains c as well.

Successful Mdr-Tb Treatment Regimens Including Amikacin Are Associated With High Rates Of Hearing Loss, Chawangwa Modongo, Rafal S. Sobota, Boikobo Kesenogile, Ronald Ncube

Dartmouth Scholarship

Aminoglycosides are a critical component of multidrug-resistant tuberculosis (MDR-TB) treatment but data on their efficacy and adverse effects in Botswana is scarce. We determined the effect of amikacin on treatment outcomes and development of hearing loss in MDR-TB patients. Patients started on MDR-TB treatment between 2006 and 2012 were included. Multivariate analysis was used to determine the effect of amikacin on treatment outcomes and development of hearing loss.

Generalized Quantile Treatment Effect, Sergio Venturini, Francesca Dominici, Giovanni Parmigiani

Harvard University Biostatistics Working Paper Series

No abstract provided.

Planarity Of Whitney Levels, Jorbe Bustamante, W. J. Charatonik, Raul Escobedo

Mathematics and Statistics Faculty Research & Creative Works

First, we characterize all locally connected continua whose all Whitney levels are planar. Second, we show by example that planarity is not a (strong) Whitney reversible property. This answers a question from Illanes-Nadler book [2].

A Bayesian Approach To Joint Modeling Of Menstrual Cycle Length And Fecundity, Kirsten J. Lum, Rajeshwari Sundaram, Germaine M. Buck-Louis, Thomas A. Louis

Johns Hopkins University, Dept. of Biostatistics Working Papers

Female menstrual cycle length is thought to play an important role in couple fecundity, or the biologic capacity for reproduction irrespective of pregnancy intentions. A complete assessment of the association between menstrual cycle length and fecundity requires a model that accounts for multiple risk factors (both male and female) and the couple's intercourse pattern relative to ovulation. We employ a Bayesian joint model consisting of a mixed effects accelerated failure time model for longitudinal menstrual cycle lengths and a hierarchical model for the conditional probability of pregnancy in a menstrual cycle given no pregnancy in previous cycles of trying, in …

Application Of Bayesian Networks In Consumer Service Industry, Yuan Gao

Open Access Theses

Gao, Yuan. M.S.I.E., Purdue University. December 2014. Application of Bayesian Networks in Consumer Service Industry. Major professor: Vincent G. Duffy The purpose of the present study is to explore the application of Bayesian networks in the consumer service industry to model causal relationships within complex risk factor structures using aggregate data. An analysis of the Hawaii tourism market was conducted to find out how visitor characteristics affect their behavior and experience as consumers during the trips, and influence the tourism market outcomes represented by measurable factors. Two hypotheses were proposed regarding the use of aggregate data and the influence of …