Applied Statistics Commons^™

Estimating Vehicular Traffic Intensity With Deep Learning And Semantic Segmentation, Logan Bradley-Trietsch

The Journal of Purdue Undergraduate Research

No abstract provided.

High Wind Alerts: A System Created With Observations From The X-Band Teaching And Research Radar, Lauren Warner

The Journal of Purdue Undergraduate Research

Following the August 13, 2011, Indiana State Fair stage collapse tragedy, caused by a wind gust from an approaching thunderstorm, Purdue University enforced a wind speed restriction of 30 mph (13 m s-1) for tents at outdoor events. During these events, volunteers stand outside with handheld anemometers, measuring and reporting when the wind speeds exceed this limit. In this study, we report testing of a new system to automate high-wind alerts based on observations from a Doppler radar, the X-band Teaching and Research Radar (XTRRA), near Purdue’s campus. XTRRA scans over campus at low elevations approximately every 5 minutes. Using …

A New Two-Parametric ‘Useful’ Fuzzy Information Measure And Its Properties, Saima Manzoor Sofi, Safina Peerzada, Mirza Abdul Khalique Baig

Journal of Modern Applied Statistical Methods

A ‘useful’ fuzzy measure of order α and type β is developed. Its validity established with a numerical example.

Cell Assembly Detection In Low Firing-Rate Spike Train Data, Phan Minh Duc Truong

Mathematics Theses and Dissertations

Cell assemblies, defined as groups of neurons forming temporal spike coordination, are thought to be fundamental units supporting major cognitive functions. However, detecting cell assemblies is challenging since they can occur at a range of time scales and with a range of precisions, from synchronous spikes to co-variations in firing rate. In this dissertation, we use a recently published cell assembly detection (CAD) algorithm that is capable of detecting assemblies at a range of time scales and precisions. We first showed that the CAD method can be applied to sparser spike train data than what have previously been reported. This …

A New Two Parametric Weighted Generalized Entropy For Lifetime Distributions, Bilal Ahmad Bhat, Mirza Abdul Khaliq Baig

Journal of Modern Applied Statistical Methods

The concept of weighted generalized entropy and its dynamic residual (version) is developed. The general expressions of these two uncertainty measures corresponding to some well-known lifetime distributions are derived. It is shown that the proposed dynamic entropy determines the survival function uniquely. Some significant properties and inequalities of this dynamic entropy are also discussed.

Analyzing The Fractal Dimension Of Various Musical Pieces, Nathan Clark

Industrial Engineering Undergraduate Honors Theses

One of the most common tools for evaluating data is regression. This technique, widely used by industrial engineers, explores linear relationships between predictors and the response. Each observation of the response is a fixed linear combination of the predictors with an added error element. The method is built on the assumption that this error is normally distributed across all observations and has a mean of zero. In some cases, it has been found that the inherent variation is not the result of a random variable, but is instead the result of self-symmetric properties of the observations. For data with these …

A Novel Correction For The Adjusted Box-Pierce Test — New Risk Factors For Emergency Department Return Visits Within 72 Hours For Children With Respiratory Conditions — General Pediatric Model For Understanding And Predicting Prolonged Length Of Stay, Sidy Danioko

Computational and Data Sciences (PhD) Dissertations

This thesis represents the results of three research projects that underline the breadth and depth of my interests.

Firstly, I devoted some efforts to the well-known Box-Pierce goodness-of-fit tests for time series models which has been an important research topic over the last few decades. All previously proposed tests are focused on changes of the test statistics. Instead, I adopted a different approach that takes the best performing test and modifying the rejection region. Thus, I developed a semiparametric correction of the Adjusted Box-Pierce test that attains the best I error rates for all sample sizes and lags and outperforms …

A Geochemical And Statistical Investigation Of The Big Four Springs Region In Southern Missouri, Jordan Jasso Vega

Graduate Theses/Dissertations

The Big Four Springs region hosts four major first-order magnitude springs in southern Missouri and northern Arkansas. These springs are Big Spring (Carter County, MO), Greer Spring (Oregon County, MO), Mammoth Spring (Fulton County, AR), and Hodgson Mill Spring (Ozark County, MO). Based on historic dye traces and hydrogeological investigations, these springs drain an area of approximately 1500 square miles and collectively discharge an average of 780 million gallons of water per day. The rocks from youngest to oldest that are found in Big Four Springs region are the Cotter and Jefferson City Dolomite (Ordovician), Roubidoux Formation (Ordovician), Gasconade Dolomite …

Linear Methods For Regression With Small Sample Sizes Relative To The Number Of Variables., Rajesh Sikder

Electronic Theses and Dissertations

In data sets where there are a small number of observations but a large number of variables observed for each observation, ordinary least squares estimation cannot be used for regression models. There are many alternative including stepwise regression, penalized methods such as ridge regression and the LASSO, and methods based on derived inputs such as principal components regression and partial least squares regression. In this thesis, these five methods are described. K-fold cross validation is also discussed as a way for determining regularization parameters for each method. The performance of these methods in estimation and prediction is also examined through …

Effects Of Gender And Socioeconomic Status Towards Form Four Pupils’ Statistical Thinking Abilities, Jing Hui Ong

Student Works (2020-2029)

Statistical thinking abilities of Form Four students are not known as there is a lack of studies that measures it. Despite the fact that the students were exposed to the same curriculum and pedagogy, the thinking abilities of students varied in terms of gender. There is also uncertainty in whether socio-economic status is a cause that affects statistical thinking abilities due to lack of research in that particular area. This study aimed to examine the effects of gender and socio-economic status on statistical thinking abilities of Form Four students. To answer the three research questions of this study, survey descriptive …

Even Order Ranked Set Sampling With Auxiliary Variable, Muhammad Tayyab, Muhammad Noor Ul-Amin, Muhammad Hanif

Journal of Modern Applied Statistical Methods

Even order ranked set sampling (EORSS) is a novel proposed ranked set sampling scheme connected with an auxiliary variable correlated with the study variable. This scheme quantifies only the one sampling unit which is at even position from each ranking set by employing specific criteria. The performance of the ratio estimator under EORSS is compared to its contemporary estimators in simple random sampling (SRS), ranked set sampling (RSS), median ranked set sampling (MRSS) and quartile ranked set sampling (QRSS) exploiting the same number of quantified units. The simulation results proved that EORSS is an efficient alternative sampling scheme for ratio …

Objectives Driven Participatory Evaluation Model, Dustin R. Saalman

Journal of Modern Applied Statistical Methods

The ability to complete program evaluations of educational programming is typically restricted by the availability of resources, such as time, money and a trained evaluator. Although not a replacement for trained evaluators, promoting evaluative capacity and evaluative thinking within an organization can help mitigate this gap between talent and resources. Participatory evaluation is purported to increase organizational learning and promote evaluative thinking within an organization (Cousins & Whitmore, 1998). Objectives oriented evaluation is an easily understood evaluation method which provides a refined focus program outcome (Madaus & Stufflebeam, 1989). Using an internal evaluation of a new faculty onboarding course at …

Statistical Methodology To Establish A Benchmark For Evaluating Antimicrobial Resistance Genes Through Real Time Pcr Assay, Enakshy Dutta

Department of Statistics: Dissertations, Theses, and Student Research

Novel diagnostic tests are usually compared with gold standard tests for evaluating diagnostic accuracy. For assessing antimicrobial resistance (AMR) to bovine respiratory disease (BRD) pathogens, phenotypic broth microdilution method is used as gold standard (GS). The objective of the thesis is to evaluate the optimal cycle threshold (Ct) generated by real-time polymerase chain reaction (rtPCR) to genes that confer resistance that will translate to the phenotypic classification of AMR. Data from two different methodologies are assessed to identify Ct that will discriminate between resistance (R) and susceptibility (S). First, the receiver operating characteristic (ROC) curve was used to determine the …

Maximum Likelihood Estimations Based On Upper Record Values For Probability Density Function And Cumulative Distribution Function In Exponential Family And Investigating Some Of Their Properties, Saman Hosseini, Parviz Nasiri, Sharad Damodar Gore

Journal of Modern Applied Statistical Methods

A useful subfamily of the exponential family is considered. The ML estimation based on upper record values are calculated for the parameter, Cumulative Density Function, and Probability Density Function of the subfamily. The relationship between MLE based on record values and a random sample are discussed, along with some properties of these estimators, and its utility is shown for large samples.

The Comparison Between Maximum Weighted And Trimmed Likelihood Estimator Of The Simple Circular Regression Model, Ehab A. Mahmood, Habshah Midi, Abdul Ghapor Hussin

Journal of Modern Applied Statistical Methods

The Maximum Likelihood Estimator (MLE) was used to estimate unknown parameters of the simple circular regression model. However, it is very sensitive to outliers in data set. A robust method to estimate model parameters is proposed.

Bayesian Estimation Of The Parameters Of Discrete Weibull Type (I) Distribution, Samir Kamel Ashour, Mohamed Salem Abdelwahab Muiftah

Journal of Modern Applied Statistical Methods

Bayesian estimation of the continuous Weibull distribution parameters was studied by Ahmad and Ahmad (2013) under the assumption of knowing the shape parameter. Bayesian estimates are considered here of the parameters of the discrete Weibull Type I [DW(I)] distribution and are obtained under two different assumptions: when the shape parameter is known, and when both parameters are independent random variables. A Mathcad program is performed to simulate data from the DW(I) distribution considering different values of the parameters and different sample sizes, and to obtain Bayesian parameter estimates. The resulted estimates are compared to the ML and proportion estimates obtained …

The Logic Model, Participatory Evaluation And Out Of School Art Programs, Kimberly A. Kleinhans

Journal of Modern Applied Statistical Methods

The logic model and participatory evaluation are two popular methods of conducting program evaluation. Although both methods have their strengths, each has distinct weaknesses which can be ameliorated by combining them both together. The combined method is used to evaluate an out of school art program at a museum. Using both the logic model and participatory evaluation yielded beneficial results with more accurate representation of program outcomes.

A Generalized Family Of Lifetime Distributions And Survival Models, Mahmoud Aldeni, Felix Famoye, Carl Lee

Journal of Modern Applied Statistical Methods

In lifetime data, the hazard function is a common technique for describing the characteristics of lifetime distribution. Monotone increasing or decreasing, and unimodal are relatively simple hazard function shapes, which can be modeled by many parametric lifetime distributions. However, fewer distributions are capable of modeling diverse and more complicated shapes such as N-shaped, reflected N-shaped, W-shaped, and M-shaped hazard rate functions. A generalized family of lifetime distributions, the uniform-R{generalized lambda} (U-R{GL}) are introduced and the corresponding survival models are derived, and applied to two lifetime data sets. The survival model is applied to a right censored lifetime data set.

A Revised Logic Model For Educational Program Evaluation, Zsa-Zsa Booker

Journal of Modern Applied Statistical Methods

The logic model is an evaluation tool popularly used for obtaining grant funding. Its limitations make it unlike other theory driven evaluation methods. A critical examination of the logic model leads to the construction of an enriched revised logic model.

Forward And Backward Continuation Ratio Models For Ordinal Response Variables, Xing Liu, Haiyan Bai

Journal of Modern Applied Statistical Methods

There are different types of continuation ratio (CR) models for ordinal response variables. The different model equations, corresponding parameterizations, and nonequivalent results are confusing. The purpose of this study is to introduce different types of forward and backward CR models, demonstrate how to implement these models using Stata, and compare the results using data from the Educational Longitudinal Study of 2002 (ELS:2002).