Open Access. Powered by Scholars. Published by Universities.®

Applied Statistics Commons

Open Access. Powered by Scholars. Published by Universities.®

2,844 Full-Text Articles 3,773 Authors 765,903 Downloads 126 Institutions

All Articles in Applied Statistics

Faceted Search

2,844 full-text articles. Page 1 of 74.

A Latent Spatial Piecewise Exponential Model For Interval-Censored Disease Surveillance Data With Time-Varying Covariates And Misclassification, Yaxuan Sun, Chong Wang, William Q. Meeker, Max Morris, Marisa L. Rotolo, Jeffery Zimmerman 2019 Iowa State University

A Latent Spatial Piecewise Exponential Model For Interval-Censored Disease Surveillance Data With Time-Varying Covariates And Misclassification, Yaxuan Sun, Chong Wang, William Q. Meeker, Max Morris, Marisa L. Rotolo, Jeffery Zimmerman

Veterinary Diagnostic and Production Animal Medicine Publications

Understanding the dynamics of disease spread is critical to achieving effective animal disease surveillance. A major challenge in modeling disease spread is the fact that the true disease status cannot be known with certainty due to the imperfect diagnostic sensitivity and specificity of the tests used to generate the disease surveillance data. Other challenges in modeling such data include interval censoring, relating disease spread to distance between units, and incorporating time-varying covariates, which are the unobserved disease statuses. We propose a latent spatial piecewise exponential model (PEX) with misclassification of events to address the challenges in modeling such disease surveillance ...


A Proficient Two-Stage Stratified Randomized Response Strategy, Tanveer A. Tarray, Housila P. Singh 2018 Islamic University of Science and Technology, Awantipora, India

A Proficient Two-Stage Stratified Randomized Response Strategy, Tanveer A. Tarray, Housila P. Singh

Journal of Modern Applied Statistical Methods

A stratified randomized response model based on R. Singh, Singh, Mangat, and Tracy (1995) improved two-stage randomized response strategy is proposed. It has an optimal allocation and large gain in precision. Conditions are obtained under which the proposed model is more efficient than R. Singh et al. (1995) and H. P. Singh and Tarray (2015) models. Numerical illustrations are also given in support of the present study.


Extended Method For Several Dichotomous Covariates To Estimate The Instantaneous Risk Function Of The Aalen Additive Model, Luciane Teixeira Passos Giarola, Mario Javier Ferrua Vivanco, Marcelo Angelo Cirillo, Fortunato Silva Menezes 2018 Federal University of São João del Rei

Extended Method For Several Dichotomous Covariates To Estimate The Instantaneous Risk Function Of The Aalen Additive Model, Luciane Teixeira Passos Giarola, Mario Javier Ferrua Vivanco, Marcelo Angelo Cirillo, Fortunato Silva Menezes

Journal of Modern Applied Statistical Methods

The instantaneous risk function of Aalen’s model is estimated considering dichotomous covariates, using parametric accumulated risk functions to smooth cumulative risk of Aalen by grouping the individuals into sets named parcels. This methodology can be used for data with dichotomous covariates.


Simple Unbalanced Ranked Set Sampling For Mean Estimation Of Response Variable Of Developmental Programs, Girish Chandra, Dinesh S. Bhoj, Rajiv Pandey 2018 Indian Council of Forestry Research and Education

Simple Unbalanced Ranked Set Sampling For Mean Estimation Of Response Variable Of Developmental Programs, Girish Chandra, Dinesh S. Bhoj, Rajiv Pandey

Journal of Modern Applied Statistical Methods

An unbalanced ranked set sampling (RSS) procedure on the skewed survey variable is proposed to estimate the population mean of a response variable from the area of developmental programs which are generally implemented under different phases. It is based on the unbalanced RSS under linear impacts of the program and is compared with the estimators based on simple random sampling (SRS) and balanced RSS. It is shown that the relative precision of the proposed estimator is higher than those of the estimators based on SRS and balanced RSS for three chosen skewed distributions of survey variables.


Sequential Inference For Hidden Markov Models, Michael Ellis 2018 University of Arkansas, Fayetteville

Sequential Inference For Hidden Markov Models, Michael Ellis

Theses and Dissertations

In many applications data are collected sequentially in time with very short time intervals between observations. If one is interested in using new observations as they arrive in time then non-sequential Bayesian inference methods, such as Markov Chain Monte Carlo (MCMC) sampling, can be too slow. Increasingly, state space models are being used to model nonlinear and non-Gaussian systems. The structure of state space models allows for sequential Bayesian inference so that an approximation to the posterior distribution of interest can be updated as new observations arrive. In special cases, the exact posterior distribution can be updated through conjugate Bayesian ...


A Generative Statistical Approach For Data Classification In A Biologically Inspired Design Tool, Marvin Manuel Arroyo Rujano 2018 University of Arkansas, Fayetteville

A Generative Statistical Approach For Data Classification In A Biologically Inspired Design Tool, Marvin Manuel Arroyo Rujano

Theses and Dissertations

The objective of the research this thesis describes is to find a way to classify text-based descriptions of biological adaption to support Biologically Inspired design. Biologically inspired design is a fairly new field with ongoing research. There are different tools to assist designers and biologists in bio-inspired design. Some of the most common are BioTRIZ and AskNature. In recent years, more tools have been proposed to aid and make research in the field easier, for example, the Biologically Inspired Adaptive System Design (BIASD) tool. This tool was designed with the goal of helping designers in early design stages generate more ...


Comparing Performance Of Gene Set Test Methods Using Biologically Relevant Simulated Data, Richard M. Lambert 2018 Utah State University

Comparing Performance Of Gene Set Test Methods Using Biologically Relevant Simulated Data, Richard M. Lambert

All Graduate Theses and Dissertations

Today we know that there are many genetically driven diseases and health conditions.These problems often manifest only when a set of genes are either active or inactive. Recent technology allows us to measure the activity level of genes in cells, which we call gene expression. It is of great interest to society to be able to statistically compare the gene expression of a large number of genes between two or more groups. For example, we may want to compare the gene expression of a group of cancer patients with a group of non-cancer patients to better understand the genetic ...


Spatio-Temporal Reconstruction Of Remote Sensing Observations, Kamrul Khan 2018 University of Arkansas, Fayetteville

Spatio-Temporal Reconstruction Of Remote Sensing Observations, Kamrul Khan

Theses and Dissertations

The USDA Forest Service aims to use satellite imagery for monitoring and predicting changes in forest conditions over time within the country. We specifically focus on a 230, 400 hectares region in north-central Wisconsin between 2003 - 2012. The auxiliary data collected from the satellite imagery of this region are relatively dense in space and time and can be used to efficiently predict how the forest condition changed over that decade. However, these records have a significant proportion of missing values due to weather conditions and system failures. To fill in these missing values, we build spaciotemporal models based on fixed ...


Cronbach's Alpha Under Insufficient Effort Responses: An Analytic Approach, Stephen W. Carden, Trevor R. Camper, Nicholas S. Holtzman 2018 Georgia Southern University

Cronbach's Alpha Under Insufficient Effort Responses: An Analytic Approach, Stephen W. Carden, Trevor R. Camper, Nicholas S. Holtzman

Stephen W. Carden

Surveys commonly suffer from insufficient effort responding (IER). If not accounted for, IER
can cause biases and lead to false conclusions. In particular, Cronbach’s alpha has been empirically
observed to either deflate or inflate due to IER. This paper will elucidate how IER impacts Cronbach’s
alpha in a variety of situations. Previous results concerning internal consistency under mixture
models are extended to obtain a characterization of Cronbach’s alpha in terms of item validities,
average variances, and average covariances. The characterization is then applied to contaminating
distributions representing various types of IER. The discussion will provide commentary on ...


The Impact Of Sample Size In Cross-Classified Multiple Membership Multilevel Models, Hyewon Chung, Jiseon Kim, Ryoungsun Park, Hyeonjeong Jean 2018 Chungnam National University

The Impact Of Sample Size In Cross-Classified Multiple Membership Multilevel Models, Hyewon Chung, Jiseon Kim, Ryoungsun Park, Hyeonjeong Jean

Journal of Modern Applied Statistical Methods

A simulation study was conducted to examine parameter recovery in a cross-classified multiple membership multilevel model. No substantial relative bias was identified for the fixed effect or level-one variance component estimates. However, the level-two cross-classification multiple membership factor variance components were substantially biased with relatively fewer groups.


An Introduction To Psychological Statistics, Garett C. Foster, David Lane, David Scott, Mikki Hebl, Rudy Guerra, Dan Osherson, Heidi Zimmer 2018 University of Missouri-St. Louis

An Introduction To Psychological Statistics, Garett C. Foster, David Lane, David Scott, Mikki Hebl, Rudy Guerra, Dan Osherson, Heidi Zimmer

Open Educational Resources Collection

We are constantly bombarded by information, and finding a way to filter that information in an objective way is crucial to surviving this onslaught with your sanity intact. This is what statistics, and logic we use in it, enables us to do. Through the lens of statistics, we learn to find the signal hidden in the noise when it is there and to know when an apparent trend or pattern is really just randomness. The study of statistics involves math and relies upon calculations of numbers. But it also relies heavily on how the numbers are chosen and how the ...


Bias Assessment And Reduction In Kernel Smoothing, Wenkai Ma 2018 The University of Western Ontario

Bias Assessment And Reduction In Kernel Smoothing, Wenkai Ma

Electronic Thesis and Dissertation Repository

When performing local polynomial regression (LPR) with kernel smoothing, the choice of the smoothing parameter, or bandwidth, is critical. The performance of the method is often evaluated using the Mean Square Error (MSE). Bias and variance are two components of MSE. Kernel methods are known to exhibit varying degrees of bias. Boundary effects and data sparsity issues are two potential problems to watch for. There is a need for a tool to visually assess the potential bias when applying kernel smooths to a given scatterplot of data. In this dissertation, we propose pointwise confidence intervals for bias and demonstrate a ...


Analysis Of Ranked Gene Tree Probability Distributions Under The Coalescent Process For Detecting Anomaly Zones, Anastasiia Kim 2018 University of New Mexico

Analysis Of Ranked Gene Tree Probability Distributions Under The Coalescent Process For Detecting Anomaly Zones, Anastasiia Kim

Shared Knowledge Conference

In phylogenetic studies, gene trees are used to reconstruct species tree. Under the multispecies coalescent model, gene trees topologies may differ from that of species trees. The incorrect gene tree topology (one that does not match the species tree) that is more probable than the correct one is termed anomalous gene tree (AGT). Species trees that can generate such AGTs are said to be in the anomaly zone (AZ). In this region, the method of choosing the most common gene tree as the estimate of the species tree will be inconsistent and will converge to an incorrect species tree when ...


41 - Data Exploration And Analysis For The Hemingway Measure Of Adult Connectedness, Gildardo Bautista-Maya, Ping Ye, Diane Cook 2018 University of North Georgia

41 - Data Exploration And Analysis For The Hemingway Measure Of Adult Connectedness, Gildardo Bautista-Maya, Ping Ye, Diane Cook

Georgia Undergraduate Research Conference (GURC)

Abstract:

We analyze the dataset collected from students participating in the Boy With A Ball (BWAB) program, a faith-based community outreach group, through the Hemingway Measure of Adult Connectedness©, a questionnaire measuring the social connectedness of adolescents. First, we approach the data in the conventional method provided by the Hemingway website. We then identify which questions are strong determiners in deciding whether a student has completed the BWAB program or not. With the goal of utilizing the logistic regression, we reduce the set of questions to those only identified as significant in other methods. These methods include linear regression, decision ...


Preface, weixing song 2018 Kansas State University

Preface, Weixing Song

Conference on Applied Statistics in Agriculture

Preface


Statistical Investigation Of Road And Railway Hazardous Materials Transportation Safety, Amirfarrokh Iranitalab 2018 University of Nebraska-Lincoln

Statistical Investigation Of Road And Railway Hazardous Materials Transportation Safety, Amirfarrokh Iranitalab

Civil Engineering Theses, Dissertations, and Student Research

Transportation of hazardous materials (hazmat) in the United States (U.S.) constituted 22.8% of the total tonnage transported in 2012 with an estimated value of more than 2.3 billion dollars. As such, hazmat transportation is a significant economic activity in the U.S. However, hazmat transportation exposes people and environment to the infrequent but potentially severe consequences of incidents resulting in hazmat release. Trucks and trains carried 63.7% of the hazmat in the U.S. in 2012 and are the major foci of this dissertation. The main research objectives were 1) identification and quantification of the effects ...


Probabilities Involving Standard Trirectangular Tetrahedral Dice Rolls, Rulon Olmstead, DonEliezer Baize 2018 Brigham Young University-Hawaii

Probabilities Involving Standard Trirectangular Tetrahedral Dice Rolls, Rulon Olmstead, Doneliezer Baize

Rose-Hulman Undergraduate Mathematics Journal

The goal is to be able to calculate probabilities involving irregular shaped dice rolls. Here it is attempted to model the probabilities of rolling standard tri-rectangular tetrahedral dice on a hard surface, such as a table top. The vertices and edges of a tetrahedron were projected onto the surface of a sphere centered at the center of mass of the tetrahedron. By calculating the surface areas bounded by the resultant geodesics, baseline probabilities were achieved. Using a 3D printer, dice were constructed of uniform density and the results of rolling them were recorded. After calculating the corresponding confidence intervals, the ...


Group-Lasso Estimation In High-Dimensional Factor Models With Structural Breaks, Yujie Song 2018 University of Windsor

Group-Lasso Estimation In High-Dimensional Factor Models With Structural Breaks, Yujie Song

Major Papers

In this major paper, we study the influence of structural breaks in the financial market model with high-dimensional data. We present a model which is capable of detecting changes in factor loadings, determining the number of factors and detecting the break date. We consider the case where the break date is both known and unknown and identify the type of instability. For the unknown break date case, we propose a group-LASSO estimator to determine the number of pre- and post-break factors, the break date and the existence of instability of factor loadings when the number of factor is constant. We ...


Estimation In High-Dimensional Factor Models With Structural Instabilities, Wen Gao 2018 University of Windsor

Estimation In High-Dimensional Factor Models With Structural Instabilities, Wen Gao

Major Papers

In this major paper, we use high-dimensional models to analyze macroeconomic data which is in influenced by the break point. In particular, we consider to detect the break point and study the changes of the number of factors and the factor loadings with the structural instability.

Concretely, we propose two factor models which explain the processes of pre- and post- break periods. Then, we consider the break point as known or unknown. In both situations, we derive the shrinkage estimators by minimizing the penalized least square function and calculate the estimators of the numbers of pre- and post- break factors ...


Using Cyclical Components To Improve The Forecasts Of The Stock Market And Macroeconomic Variables, Kenneth R. Szulczyk, Shibley Sadique 2018 Curtin University Malaysia

Using Cyclical Components To Improve The Forecasts Of The Stock Market And Macroeconomic Variables, Kenneth R. Szulczyk, Shibley Sadique

Journal of Modern Applied Statistical Methods

Economic variables such as stock market indices, interest rates, and national output measures contain cyclical components. Forecasting methods excluding these cyclical components yield inaccurate out-of-sample forecasts. Accordingly, a three-stage procedure is developed to estimate a vector autoregression (VAR) with cyclical components. A Monte Carlo simulation shows the procedure estimates the parameters accurately. Subsequently, a VAR with cyclical components improves the root-mean-square error of out-of-sample forecasts by 50% for a stock market model with macroeconomic variables.


Digital Commons powered by bepress