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2939 full-text articles. Page 1 of 76.

Multivariate Spectral Analysis Of Crism Data To Characterize The Composition Of Mawrth Vallis, Melissa Luna 2018 Wesleyan University

Multivariate Spectral Analysis Of Crism Data To Characterize The Composition Of Mawrth Vallis, Melissa Luna

Melissa Luna

No abstract provided.


Predicting The Next Us President By Simulating The Electoral College, Boyan Kostadinov 2018 New York City College of Technology, CUNY

Predicting The Next Us President By Simulating The Electoral College, Boyan Kostadinov

Journal of Humanistic Mathematics

We develop a simulation model for predicting the outcome of the US Presidential election based on simulating the distribution of the Electoral College. The simulation model has two parts: (a) estimating the probabilities for a given candidate to win each state and DC, based on state polls, and (b) estimating the probability that a given candidate will win at least 270 electoral votes, and thus win the White House. All simulations are coded using the high-level, open-source programming language R. One of the goals of this paper is to promote computational thinking in any STEM field by illustrating how probabilistic ...


Modeling Mayfly Nymph Length Distribution And Population Dynamics Across A Gradient Of Stream Temperatures And Stream Types, Jeremy Anthony, Jennifer Baccam, Imanuel Bier, Emily Gregg, Leif Halverson, Ryan Mulcahy, Emmanuel Okanla, Samira A. Osman, Adam R. Pancoast, Kevin C. Schultz, Alex Sushko, Jennifer Vorarath, Yia Vue, Austin Wagner, Emily Gaenzle Schilling, John M. Zobitz 2018 Augsburg College

Modeling Mayfly Nymph Length Distribution And Population Dynamics Across A Gradient Of Stream Temperatures And Stream Types, Jeremy Anthony, Jennifer Baccam, Imanuel Bier, Emily Gregg, Leif Halverson, Ryan Mulcahy, Emmanuel Okanla, Samira A. Osman, Adam R. Pancoast, Kevin C. Schultz, Alex Sushko, Jennifer Vorarath, Yia Vue, Austin Wagner, Emily Gaenzle Schilling, John M. Zobitz

Spora: A Journal of Biomathematics

We analyze a process-based temperature model for the length distribution and population over time of mayfly nymphs. Model parameters are estimated using a Markov Chain Monte Carlo parameter estimation method utilizing length distribution data at five different stream sites. Two different models (a standard exponential model and a modified Weibull model) of mayfly mortality are evaluated, where in both cases mayfly length growth is a function of stream temperature. Based on model-data comparisons to the modeled length distribution and the Bayesian Information Criterion, we found that approaches that length distribution data can reliably estimate 2–3 model parameters. Future model ...


Big Data And Parkinson’S Disease: Exploration, Analyses, And Data Challenges, Mahalakshmi SenthilarumugamVeilukandammal, Sree Nilakanta, Baskar Ganapathysubramanian, Vellareddy Anantharam, Anumantha Kanthasamy, Auriel A. Willette 2018 Iowa State University

Big Data And Parkinson’S Disease: Exploration, Analyses, And Data Challenges, Mahalakshmi Senthilarumugamveilukandammal, Sree Nilakanta, Baskar Ganapathysubramanian, Vellareddy Anantharam, Anumantha Kanthasamy, Auriel A. Willette

Mechanical Engineering Conference Presentations, Papers, and Proceedings

In healthcare, a tremendous amount of clinical and laboratory tests, imaging, prescription and medication data are being collected. Big data analytics on these data aim at early detection of disease which will help in developing preventive measures and in improving patient care. Parkinson disease is the second-most common neurodegenerative disorder in the United States. To find a cure for Parkinson's disease biological, clinical and behavioral data of different cohorts are collected, managed and propagated through Parkinson’s Progression Markers Initiative (PPMI). Applying big data technology to this data will lead to the identification of the potential biomarkers of Parkinson ...


Modeling Mayfly Nymph Length Distribution And Population Dynamics Across A Gradient Of Stream Temperatures And Stream Types, Jeremy Anthony, Jennifer Baccam, Imanuel Bier, Emily Gregg, Leif Halverson, Ryan Mulcahy, Emmanuel Okanla, Samira A. Osman, Adam R. Pancoast, Kevin C. Schultz, Alex Sushko, Jennifer Vorarath, Yia Vue, Austin Wagner, Emily Gaenzle Schilling, John Zobitz 2018 Augsburg University

Modeling Mayfly Nymph Length Distribution And Population Dynamics Across A Gradient Of Stream Temperatures And Stream Types, Jeremy Anthony, Jennifer Baccam, Imanuel Bier, Emily Gregg, Leif Halverson, Ryan Mulcahy, Emmanuel Okanla, Samira A. Osman, Adam R. Pancoast, Kevin C. Schultz, Alex Sushko, Jennifer Vorarath, Yia Vue, Austin Wagner, Emily Gaenzle Schilling, John Zobitz

Faculty Authored Articles

We analyze a process-based temperature model for the length distribution and population over time of mayfly nymphs. Model parameters are estimated using a Markov Chain Monte Carlo parameter estimation method utilizing length distribution data at five different stream sites. Two different models (a standard exponential model and a modified Weibull model) of mayfly mortality are evaluated, where in both cases mayfly length growth is a function of stream temperature. Based on model-data comparisons to the modeled length distribution and the Bayesian Information Criterion, we found that approaches that length distribution data can reliably estimate 2–3 model parameters. Future model ...


Accounting For Matching Uncertainty In Photographic Identification Studies Of Wild Animals, Amanda R. Ellis 2018 University of Kentucky

Accounting For Matching Uncertainty In Photographic Identification Studies Of Wild Animals, Amanda R. Ellis

Theses and Dissertations--Statistics

I consider statistical modelling of data gathered by photographic identification in mark-recapture studies and propose a new method that incorporates the inherent uncertainty of photographic identification in the estimation of abundance, survival and recruitment. A hierarchical model is proposed which accepts scores assigned to pairs of photographs by pattern recognition algorithms as data and allows for uncertainty in matching photographs based on these scores. The new models incorporate latent capture histories that are treated as unknown random variables informed by the data, contrasting past models having the capture histories being fixed. The methods properly account for uncertainty in the matching ...


Cross-Sectional Versus Longitudinal Designs For Function Estimation, With An Application To Cerebral Cortex Development, Philip T. Reiss 2017 New York University School of Medicine

Cross-Sectional Versus Longitudinal Designs For Function Estimation, With An Application To Cerebral Cortex Development, Philip T. Reiss

Philip T. Reiss

Motivated by studies of the development of the human cerebral cortex, we consider
the estimation of a mean growth trajectory and the relative merits of cross-sectional
and longitudinal data for that task. We define a class of relative efficiencies that
compare function estimates in terms of aggregate variance of a parametric function
estimate. These generalize the classical design effect for estimating a scalar with
cross-sectional versus longitudinal data, and in particular cases are shown to be
bounded above by it. Turning to nonparametric function estimation, we find that a
longitudinal fits may tend to have higher aggregate variance than cross-sectional ...


How Is Your Productivity Affected Based On Your App Usage?, Colette Noghreian 2017 Chapman University

How Is Your Productivity Affected Based On Your App Usage?, Colette Noghreian

Student Research Day Abstracts and Posters

As technology becomes more prominent in society, it is crucial to investigate its effect on day to day life. The purpose of this study is to determine how the amount of time spent on iPhone applications affects how productive students feel in the span of one week. Results are tested through a survey which first determines general information about the student, and then guides students to navigate their phone settings and record the battery usage of the top three applications which use up the most battery. It is hypothesized that productivity decreases as battery usage increases due to the substantial ...


Inferential Procedures For Log Logistic Distribution With Doubly Interval Censored Data, Yue Fang Loh, Jayanthi Arasan, Habshah Midi, M. R. Abu Bakar 2017 Universiti Putra Malaysia, Seri Kembangan, Malaysia

Inferential Procedures For Log Logistic Distribution With Doubly Interval Censored Data, Yue Fang Loh, Jayanthi Arasan, Habshah Midi, M. R. Abu Bakar

Journal of Modern Applied Statistical Methods

The log logistic model with doubly interval censored data is examined. Three methods of constructing confidence interval estimates for the parameter of the model were compared and discussed. The results of the coverage probability study indicated that the Wald outperformed the likelihood ratio and jackknife inferential procedures.


Study Evaluating The Alterations Caused In An Exploratory Factor Analysis When Multivariate Normal Data Is Dichotomized, Rosilei S. Novak, Jair M. Marques 2017 Federal University of Paraná, Curitiba, Brazil

Study Evaluating The Alterations Caused In An Exploratory Factor Analysis When Multivariate Normal Data Is Dichotomized, Rosilei S. Novak, Jair M. Marques

Journal of Modern Applied Statistical Methods

The relationships resulting from the dichotomization of multivariate normal data is a question that causes concern when using exploratory factor analysis. The relationships in an exploratory factor analysis are examined when multivariate normal data, generated by Monte Carlo methods, is dichotomized.


Bayesian Hypothesis Testing Of Two Normal Samples Using Bootstrap Prior Technique, Oyebayo Ridwan Olaniran, Waheed Babatunde Yahya 2017 Universiti Tun Hussein Onn Malaysia, Muar, Johor, Malaysia

Bayesian Hypothesis Testing Of Two Normal Samples Using Bootstrap Prior Technique, Oyebayo Ridwan Olaniran, Waheed Babatunde Yahya

Journal of Modern Applied Statistical Methods

The most important ingredient in Bayesian analysis is prior or prior distribution. A new prior determination method was developed under the framework of parametric empirical Bayes using bootstrap technique. By way of example, Bayesian estimations of the parameters of a normal distribution with unknown mean and unknown variance conditions were considered, as well as its application in comparing the means of two independent normal samples with several scenarios. A Monte Carlo study was conducted to illustrate the proposed procedure in estimation and hypothesis testing. Results from Monte Carlo studies showed that the bootstrap prior proposed is more efficient than the ...


End Matter, JMASM Editors 2017 Wayne State University

End Matter, Jmasm Editors

Journal of Modern Applied Statistical Methods

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On Variance Balanced Designs, Dilip Kumar Ghosh, Sangeeta Ahuja 2017 Saurashtra University Rajkot, Gujarat, India

On Variance Balanced Designs, Dilip Kumar Ghosh, Sangeeta Ahuja

Journal of Modern Applied Statistical Methods

Balanced incomplete block designs are not always possible to construct because of their parametric relations. In such a situation another balanced design, the variance balanced design, is required. This construction of binary, equal replicated variance balanced designs are discussed using the half fraction of the 2n factorial designs with smaller block sizes. This method was also extended to construct another variance balanced design by deleting the last block of the resulting variance balanced designs. Its efficiency factor compared with randomized block designs was compared and found to be highly efficient.


'Parallel Universe' Or 'Proven Future'? The Language Of Dependent Means T-Test Interpretations, Anthony M. Gould, Jean-Etienne Joullié 2017 Université Laval, Quebec City

'Parallel Universe' Or 'Proven Future'? The Language Of Dependent Means T-Test Interpretations, Anthony M. Gould, Jean-Etienne Joullié

Journal of Modern Applied Statistical Methods

Of the three kinds of two-mean comparisons which judge a test statistic against a critical value taken from a Student t-distribution, one – the repeated measures or dependent-means application – is distinctive because it is meant to assess the value of a parameter which is not part of the natural order. This absence forces a choice between two interpretations of a significant test result and the meaning of the test hypothesis. The parallel universe view advances a conditional, backward-looking conclusion. The more practical proven future interpretation is a non-conditional proposition about what will happen if an intervention is (now) applied to each ...


A Double Ewma Control Chart For The Individuals Based On A Linear Prediction, Rafael Perez Abreu, Jay R. Schaffer 2017 University of Northern California

A Double Ewma Control Chart For The Individuals Based On A Linear Prediction, Rafael Perez Abreu, Jay R. Schaffer

Journal of Modern Applied Statistical Methods

Industrial process use single and double Exponential Weighted Moving Average control charts to detect small shifts in it. Occasionally there is a need to detect small trends instead of shifts, but the effectiveness to detect small trends. A new control chart is proposed to detect a small drift.


The Impact Of Inappropriate Modeling Of Cross-Classified Data Structures On Random-Slope Models, Feifei Ye, Laura Daniel 2017 University of Pittsburgh

The Impact Of Inappropriate Modeling Of Cross-Classified Data Structures On Random-Slope Models, Feifei Ye, Laura Daniel

Journal of Modern Applied Statistical Methods

Previous studies that explored the impact of misspecification of cross-classified data structure as strictly hierarchical are limited to random intercept models. This study examined the effects of misspecification of a two-level, cross-classified, random effect model (CCREM) where both the level-1 intercept and slope were allowed to vary randomly. Results suggest that ignoring one of the crossed factors produced considerably underestimated standard errors for: 1) the regression coefficients of the level-1 predictor; 2) the inappropriately modeled predictor associated with the misspecified crossed factor; and 3) and their interaction. This misspecification also resulted in a significant inflation of the level-1 residual variances ...


A Remark For The Admissibility Of Rao’S U-Test, Z. D. Bai, C. R. Rao, M. T. Tsai 2017 Northeast Normal University, Changchun, Jilin, China

A Remark For The Admissibility Of Rao’S U-Test, Z. D. Bai, C. R. Rao, M. T. Tsai

Journal of Modern Applied Statistical Methods

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Jmasm 46: Algorithm For Comparison Of Robust Regression Methods In Multiple Linear Regression By Weighting Least Square Regression (Sas), Mohamad Shafiq, Wan Muhamad Amir, Nur Syabiha Zafakali 2017 Universiti Sains Malaysia, Kelantan, Malaysia

Jmasm 46: Algorithm For Comparison Of Robust Regression Methods In Multiple Linear Regression By Weighting Least Square Regression (Sas), Mohamad Shafiq, Wan Muhamad Amir, Nur Syabiha Zafakali

Journal of Modern Applied Statistical Methods

The aim of this study is to compare different robust regression methods in three main models of multiple linear regression and weighting multiple linear regression. An algorithm for weighting multiple linear regression by standard deviation and variance for combining different robust method is given in SAS along with an application.


Semi-Parametric Method To Estimate The Time-To-Failure Distribution And Its Percentiles For Simple Linear Degradation Model, Laila Naji Ba Dakhn, Mohammed Al-Haj Ebrahem, Omar Eidous 2017 Yarmouk University, Irbid, Jordan

Semi-Parametric Method To Estimate The Time-To-Failure Distribution And Its Percentiles For Simple Linear Degradation Model, Laila Naji Ba Dakhn, Mohammed Al-Haj Ebrahem, Omar Eidous

Journal of Modern Applied Statistical Methods

Most reliability studies obtained reliability information by using degradation measurements over time, which contains useful data about the product reliability. Parametric methods like the maximum likelihood (ML) estimator and the ordinary least square (OLS) estimator are used widely to estimate the time-to-failure distribution and its percentiles. In this article, we estimate the time-to-failure distribution and its percentiles by using a semi-parametric estimator that assumes the parametric function to have a half- normal distribution or an exponential distribution. The performance of the semi-parametric estimator is compared via simulation study with the ML and OLS estimators by using the mean square error ...


Characterizations Of Distributions By Expected Values Of Lower Record Statistics With Spacing, M. Faizan, Ziaul Haque, M. A. Ansari 2017 Aligarh Muslim University, Aligarh, India

Characterizations Of Distributions By Expected Values Of Lower Record Statistics With Spacing, M. Faizan, Ziaul Haque, M. A. Ansari

Journal of Modern Applied Statistical Methods

The characterizations of a certain class of probability distributions are established through conditional expectation of lower record values when the conditioned record value may not be the adjacent one. Some of its important deductions are also discussed.


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