# Multivariate Analysis Commons™

## All Articles in Multivariate Analysis

285 full-text articles. Page 1 of 10.

Testing Hypotheses Of Covariance Structure In Multivariate Data, 2018 NOVA University of Lisbon

#### Testing Hypotheses Of Covariance Structure In Multivariate Data, Miguel Fonseca, Arkadiusz Koziol, Roman Zmyslony

##### Electronic Journal of Linear Algebra

In this paper there is given a new approach for testing hypotheses on the structure of covariance matrices in double multivariate data. It is proved that ratio of positive and negative parts of best unbiased estimators (BUE) provide an F-test for independence of blocks variables in double multivariate models.

Application Of Jordan Algebra For Testing Hypotheses About Structure Of Mean Vector In Model With Block Compound Symmetric Covariance Structure, 2018 Faculty of Mathematics, Computer Science and Econometrics, University of Zielona Góra,

#### Application Of Jordan Algebra For Testing Hypotheses About Structure Of Mean Vector In Model With Block Compound Symmetric Covariance Structure, Roman Zmyślony, Ivan Zezula, Arkadiusz Kozioł

##### Electronic Journal of Linear Algebra

In this article authors derive test for structure of mean vector in model with block compound symmetric covariance structure for two-level multivariate observations. One possible structure is so called structured mean vector when its components remain constant over sites or over time points, so that mean vector is of the form $\boldsymbol{1}_{u}\otimes\boldsymbol{\mu}$ with $\boldsymbol{\mu}=(\mu_1,\mu_2,\ldots,\mu_m)'\in\mathbb{R}^m$. This hypothesis is tested against alternative of unstructured mean vector, which can change over sites or over time points.

Quantitative Electroencephalography For Detecting Concussions, 2018 University of Richmond

#### Quantitative Electroencephalography For Detecting Concussions, Sara Krehbiel, Kathy Hoke, Joanna Wares

##### Biology and Medicine Through Mathematics Conference

No abstract provided.

Fast Identification Of Components Commonly Used In Homemade Explosives By Spectroscopic And Chemometric Methods, 2018 Kennesaw State University

#### Fast Identification Of Components Commonly Used In Homemade Explosives By Spectroscopic And Chemometric Methods, Deidre Day Vandenbos, Huggins Msimanga, Christopher Dockery

##### Master of Science in Chemical Sciences Theses

Homemade explosives (HMEs) have become a global pandemic. This forensic research focuses on developing identification methods that can provide quick, cost effective, non-destructive analysis using portable instrumentation. These capabilities would be invaluable to first responders, military, and security officials to establish an evidentiary link between a suspect and a reference in cases of HMEs, IEDs, arson and environmental contamination.

Modern methods for quick identification of the fuels and oxidant sources used in manufacturing HMEs, include Fourier Transform Infrared (FT-IR) and Raman spectroscopy. Visual confirmation alone, however, is not strong enough to discriminate chemicals with nearly identical spectra, which occurs when ...

2018 Lynchburg College

#### Analysis Of 2016-17 Major League Soccer Season Data Using Poisson Regression With R, Ian D. Campbell

##### Undergraduate Theses and Capstone Projects

To the outside observer, soccer is chaotic with no given pattern or scheme to follow, a random conglomeration of passes and shots that go on for 90 minutes. Yet, what if there was a pattern to the chaos, or a way to describe the events that occur in the game quantifiably. Sports statistics is a critical part of baseball and a variety of other of today’s sports, but we see very little statistics and data analysis done on soccer. Of this research, there has been looks into the effect of possession time on the outcome of a game, the ...

Longitudinal Tracking Of Physiological State With Electromyographic Signals., 2018 University of Louisville

#### Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard

##### Electronic Theses and Dissertations

Electrophysiological measurements have been used in recent history to classify instantaneous physiological configurations, e.g., hand gestures. This work investigates the feasibility of working with changes in physiological configurations over time (i.e., longitudinally) using a variety of algorithms from the machine learning domain. We demonstrate a high degree of classification accuracy for a binary classification problem derived from electromyography measurements before and after a 35-day bedrest. The problem difficulty is increased with a more dynamic experiment testing for changes in astronaut sensorimotor performance by taking electromyography and force plate measurements before, during, and after a jump from a small ...

Analysis Challenges For High Dimensional Data, 2018 The University of Western Ontario

#### Analysis Challenges For High Dimensional Data, Bangxin Zhao

##### Electronic Thesis and Dissertation Repository

In this thesis, we propose new methodologies targeting the areas of high-dimensional variable screening, influence measure and post-selection inference. We propose a new estimator for the correlation between the response and high-dimensional predictor variables, and based on the estimator we develop a new screening technique termed Dynamic Tilted Current Correlation Screening (DTCCS) for high dimensional variables screening. DTCCS is capable of picking up the relevant predictor variables within a finite number of steps. The DTCCS method takes the popular used sure independent screening (SIS) method and the high-dimensional ordinary least squares projection (HOLP) approach as its special cases.

Two methods ...

2018 University of Texas at Tyler

#### Initial Evidence Of Construct Validity Of Data From A Self-Assessment Instrument Of Technological Pedagogical Content Knowledge (Tpack) In 2-Year Public College Faculty In Texas, Kristin C. Scott

##### Human Resource Development Theses and Dissertations

Technological pedagogical content knowledge (TPACK) has been studied in K-12 faculty in the U.S. and around the world using survey methodology. Very few studies of TPACK in post-secondary faculty have been conducted and no peer-reviewed studies in U.S. post-secondary faculty have been published to date. The present study is the first reliability and validity of data from a TPACK survey to be conducted with a large sample of U.S. post-secondary faculty. The professorate of 2-year public college faculty in Texas will help their institutions meet the goals of the state’s higher education strategic plan, 60x30TX. In ...

Robust Multivariate Nonparametric Tests For Detection Of Two-Sample Location Shift In Clinical Trials, 2018 Southern University of Science and Technology

#### Robust Multivariate Nonparametric Tests For Detection Of Two-Sample Location Shift In Clinical Trials, Xuejun Jiang, Xu Guo, Ning Zhang, Bo Wang, Bo Zhang

##### Open Access Articles

This article presents and investigates performance of a series of robust multivariate nonparametric tests for detection of location shift between two multivariate samples in randomized controlled trials. The tests are built upon robust estimators of distribution locations (medians, Hodges-Lehmann estimators, and an extended U statistic) with both unscaled and scaled versions. The nonparametric tests are robust to outliers and do not assume that the two samples are drawn from multivariate normal distributions. Bootstrap and permutation approaches are introduced for determining the p-values of the proposed test statistics. Simulation studies are conducted and numerical results are reported to examine performance of ...

2018 University of Utah

#### Using Random Forests To Describe Equity In Higher Education: A Critical Quantitative Analysis Of Utah’S Postsecondary Pipelines, Tyler Mcdaniel

##### Butler Journal of Undergraduate Research

The following work examines the Random Forest (RF) algorithm as a tool for predicting student outcomes and interrogating the equity of postsecondary education pipelines. The RF model, created using longitudinal data of 41,303 students from Utah's 2008 high school graduation cohort, is compared to logistic and linear models, which are commonly used to predict college access and success. Substantially, this work finds High School GPA to be the best predictor of postsecondary GPA, whereas commonly used ACT and AP test scores are not nearly as important. Each model identified several demographic disparities in higher education access, most significantly ...

2018 Florida International University

#### An Investigation Of The Effects Of Taking Remedial Math In College On Degree Attainment And College Gpa Using Multiple Imputation And Propensity Score Matching, Meghan A. Clovis

##### FIU Electronic Theses and Dissertations

Enrollment in degree-granting postsecondary institutions in the U.S. is increasing, as are the numbers of students entering academically underprepared. Students in remedial mathematics represent the largest percentage of total enrollment in remedial courses, and national statistics indicate that less than half of these students pass all of the remedial math courses in which they enroll. In response to the low pass rates, numerous studies have been conducted into the use of alternative modes of instruction to increase passing rates. Despite myriad studies into course redesign, passing rates have seen no large-scale improvement. Lacking is a thorough investigation into preexisting ...

2018 Wesleyan University

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

##### Melissa Luna

No abstract provided.

Essentials Of Structural Equation Modeling, 2018 Istanbul Commerce University

#### Essentials Of Structural Equation Modeling, Mustafa Emre Civelek

##### Zea E-Books

Structural Equation Modeling is a statistical method increasingly used in scientific studies in the fields of Social Sciences. It is currently a preferred analysis method, especially in doctoral dissertations and academic researches. However, since many universities do not include this method in the curriculum of undergraduate and graduate courses, students and scholars try to solve the problems they encounter by using various books and internet resources.

This book aims to guide the researcher who wants to use this method in a way that is free from math expressions. It teaches the steps of a research program using structured equality modeling ...

Building A Better Risk Prevention Model, 2018 Houston County Schools

#### Building A Better Risk Prevention Model, Steven Hornyak

##### National Youth-At-Risk Conference Savannah

This presentation chronicles the work of Houston County Schools in developing a risk prevention model built on more than ten years of longitudinal student data. In its second year of implementation, Houston At-Risk Profiles (HARP), has proven effective in identifying those students most in need of support and linking them to interventions and supports that lead to improved outcomes and significantly reduces the risk of failure.

Optimal Stratification And Allocation For The June Agricultural Survey, 2018 Iowa State University

#### Optimal Stratification And Allocation For The June Agricultural Survey, Cigna, Hejian Sang, Zhengyuan Zhu, Stephanie Zimmer

##### Statistics Publications

A computational approach to optimal multivariate designs with respect to stratification and allocation is investigated under the assumptions of fixed total allocation, known number of strata, and the availability of administrative data correlated with thevariables of interest under coefficient-of-variation constraints. This approach uses a penalized objective function that is optimized by simulated annealing through exchanging sampling units and sample allocations among strata. Computational speed is improved through the use of a computationally efficient machine learning method such as K-means to create an initial stratification close to the optimal stratification. The numeric stability of the algorithm has been investigated and parallel ...

2018 The University of Western Ontario

#### Modelling The Common Risk Among Equities Using A New Time Series Model, Jingjia Chu

##### Electronic Thesis and Dissertation Repository

A new additive structure of multivariate GARCH model is proposed where the dynamic changes of the conditional correlation between the stocks are aggregated by the common risk term. The observable sequence is divided into two parts, a common risk term and an individual risk term, both following a GARCH type structure. The conditional volatility of each stock will be the sum of these two conditional variance terms. All the conditional volatility of the stock can shoot up together because a sudden peak of the common volatility is a sign of the system shock.

We provide sufficient conditions for strict stationarity ...

2018 Missouri State University

#### Chemical And Statistical Analysis Of Karst Groundwater Basin Signatures - Springfield, Mo, Benjamin E. Lockwood

Springfield, MO is located on the Springfield Plateau physiographic province. The Springfield plateau contains a number of Mississippian aged units and is mainly capped by the Burlington-Keokuk Formation. The Burlington-Keokuk is a highly fossiliferous limestone with nodular and interbedded chert. Beneath the Burlington-Keokuk lies the Elsey, Reeds Spring, and Pierson Formations respectively which comprise the Springfield Plateau aquifer hydrostratigraphic unit. Within the Springfield Plateau aquifer, a well-developed karst system includes springs, sinkholes, and caves. The Springfield Plateau aquifer is the predominant source for springs and seeps in the Springfield area. The purpose of this study was to understand the differences ...

Partially Linear Functional Additive Models For Multivariate Functional Data, 2018 Texas A&M University

#### Partially Linear Functional Additive Models For Multivariate Functional Data, Raymond K.W. Wong, Yehua Li, Zhengyuan Zhu

##### Statistics Publications

We investigate a class of partially linear functional additive models (PLFAM) that predicts a scalar response by both parametric effects of a multivariate predictor and nonparametric effects of a multivariate functional predictor. We jointly model multiple functional predictors that are cross-correlated using multivariate functional principal component analysis (mFPCA), and model the nonparametric effects of the principal component scores as additive components in the PLFAM. To address the high dimensional nature of functional data, we let the number of mFPCA components diverge to infinity with the sample size, and adopt the COmponent Selection and Smoothing Operator (COSSO) penalty to select relevant ...