Misspecification Of Variants Of Autoregressive Garch Models And Effect On In-Sample Forecasting, 2016 Department Of Statistics, University Of Ibadan, Ibadan, Nigeria
Misspecification Of Variants Of Autoregressive Garch Models And Effect On In-Sample Forecasting, Olusanya E. Olubusoye, Olaoluwa S. Yaya, Oluwadare O. Ojo
Journal of Modern Applied Statistical Methods
Generally, in empirical financial studies, the determination of the true conditional variance in GARCH modelling is largely subjective. In this paper, we investigate the consequences of choosing a wrong conditional variance specification. The methodology involves specifying a true conditional variance and then simulating data to conform to the true specification. The estimation is then carried out using the true specification and other plausible specification that are appealing to the researcher, using model and forecast evaluation criteria for assessing performance. The results show that GARCH model could serve as better alternative to other asymmetric volatility models.
Improved Ridge Estimator In Linear Regression With Multicollinearity, Heteroscedastic Errors And Outliers, 2016 Y C Mahavidyalaya, Halkarni, Tal-Chandgad, Kolhapur, Maharashtra, India
Improved Ridge Estimator In Linear Regression With Multicollinearity, Heteroscedastic Errors And Outliers, Ashok Vithoba Dorugade
Journal of Modern Applied Statistical Methods
This paper introduces a new estimator, of ridge parameter k for ridge regression and then evaluated by Monte Carlo simulation. We examine the performance of the proposed estimators compared with other well-known estimators for the model with heteroscedastics and/or correlated errors, outlier observations, non-normal errors and suffer from the problem of multicollinearity. It is shown that proposed estimators have a smaller MSE than the ordinary least squared estimator (LS), Hoerl and Kennard (1970) estimator (RR), jackknifed modified ridge (JMR) estimator, and Jackknifed Ridge M‑estimator (JRM).
Estimation Of Parameters Of Misclassified Size Biased Borel Distribution, 2016 H L Institute of Commerce, Ahmedabad University, Gujarat, India
Estimation Of Parameters Of Misclassified Size Biased Borel Distribution, Bhaktida S. Trivedi, M. N. Patel
Journal of Modern Applied Statistical Methods
A misclassified size-biased Borel Distribution (MSBBD), where some of the observations corresponding to x = c + 1 are wrongly reported as x = c with probability α, is defined. Various estimation methods like the method of maximum likelihood (ML), method of moments, and the Bayes estimation for the parameters of the MSBB distribution are used. The performance of the estimators are studied using simulated bias and simulated risk. Simulation studies are carried out for different values of the parameters and sample size.
Bayesian Analysis Of Generalized Exponential Distribution, 2016 University of Kashmir, Jammu and Kashmir, India
Bayesian Analysis Of Generalized Exponential Distribution, Saima Naqash, S. P. Ahmad, Aquil Ahmed
Journal of Modern Applied Statistical Methods
Bayesian estimators of unknown parameters of a two parameter generalized exponential distribution are obtained based on non-informative priors using different loss functions.
Hierarchical Bayes Estimation Of Reliability Indexes Of Cold Standby Series System Under General Progressive Type Ii Censoring Scheme, 2016 Department of Statistics, H. L. Institute of Commerce, Ahmedabad University
Hierarchical Bayes Estimation Of Reliability Indexes Of Cold Standby Series System Under General Progressive Type Ii Censoring Scheme, D. R. Barot, M. N. Patel
Journal of Modern Applied Statistical Methods
In this paper, hierarchical Bayes approach is presented for estimation and prediction of reliability indexes and remaining lifetimes of a cold standby series system under general progressive Type II censoring scheme. A simulation study has been carried out for comparison purpose. The study will help reliability engineers in various industrial series system setups.
Jmasm41: An Alternative Method For Multiple Linear Model Regression Modeling, A Technical Combining Of Robust, Bootstrap And Fuzzy Approach (Sas), 2016 Universiti Sains Malaysia
Jmasm41: An Alternative Method For Multiple Linear Model Regression Modeling, A Technical Combining Of Robust, Bootstrap And Fuzzy Approach (Sas), Wan Muhamad Amir W Ahmad, Mohamad Arif Awang Nawi, Nor Azlida Aleng, Mohamad Shafiq
Journal of Modern Applied Statistical Methods
Research on modeling is becoming popular nowadays, there are several of analyses used in research for modeling and one of them is known as applied multiple linear regressions (MLR). To obtain a bootstrap, robust and fuzzy multiple linear regressions, an experienced researchers should be aware the correct method of statistical analysis in order to get a better improved result. The main idea of bootstrapping is to approximate the entire sampling distribution of some estimator. To achieve this is by resampling from our original sample. In this paper, we emphasized on combining and modeling using bootstrapping, robust and fuzzy regression methodology. …
Jmasm42: An Alternative Algorithm And Programming Implementation For Least Absolute Deviation Estimator Of The Linear Regression Models (R), 2016 Federal University of Petroleum Resources, Effurun, Delta State, Nigeria.
Jmasm42: An Alternative Algorithm And Programming Implementation For Least Absolute Deviation Estimator Of The Linear Regression Models (R), Suraju Olaniyi Ogundele, J. I. Mbegbu, C. R. Nwosu
Journal of Modern Applied Statistical Methods
We propose a least absolute deviation estimation method that produced a least absolute deviation estimator of parameter of the linear regression model. The method is as accurate as existing method.
A Generalization Of The Weibull Distribution With Applications, 2016 University of Petra, Amman, Jordan
A Generalization Of The Weibull Distribution With Applications, Maalee Almheidat, Carl Lee, Felix Famoye
Journal of Modern Applied Statistical Methods
The Lomax-Weibull distribution, a generalization of the Weibull distribution, is characterized by four parameters that describe the shape and scale properties. The distribution is found to be unimodal or bimodal and it can be skewed to the right or left. Results for the non-central moments, limiting behavior, mean deviations, quantile function, and the mode(s) are obtained. The relationships between the parameters and the mean, variance, skewness, and kurtosis are provided. The method of maximum likelihood is proposed for estimating the distribution parameters. The applicability of this distribution to modeling real life data is illustrated by three examples and the results …
The Mechanics Of Clearance In A Non-Newtonian Lubrication Layer, 2016 Montclair State University
The Mechanics Of Clearance In A Non-Newtonian Lubrication Layer, Bong Jae Chung, Douglas Platt, Ashuwin Vaidya
Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works
This paper investigates the mechanics of clearance of an embedded particle in a lubrication layer of viscoelastic fluid. We show theoretically that in a slider bearing domain containing a viscoelastic fluid, the oscillating shearing motion of a wall aids in transporting away any embedded particle towards the moving boundary. The impact of geometry and material properties of the fluid layer are explored by coupling theoretical and numerical methods. Our approach suggests a possible mechanism by which the human eye could clear out any debris beneath the eyelid, under responsive blinking. Our simplified analysis brings to bear interesting approaches from physics …
Multiscale Wind Modelling For Sustainability And Resilience, 2016 The University of Western Ontario
Multiscale Wind Modelling For Sustainability And Resilience, Djordje Romanic
Electronic Thesis and Dissertation Repository
The research presented herein is a mix of meteorological and wind engineering disciplines. In many cases, there is a gap between these two fields and this thesis is an attempt to bridge that gap through multiscale wind modelling approaches. Data and methods used in this study cover a multitude of spatial and temporal scales. Applications are in the fields of sustainability and resilience. This relationship between multiscale wind modelling and sustainability and resilience is investigated examining several case studies of three different developments: urban, rural and coastal.
An urban wind modelling methodology is proposed and applied for a specific development …
Human Exposure Modeling Using Sheds, 2016 Alion Science & Technology Inc
Human Exposure Modeling Using Sheds, Luther Smith, William Graham Glen
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Advanced Data Analysis - Lecture Notes, 2016 University of New Mexico
Advanced Data Analysis - Lecture Notes, Erik B. Erhardt, Edward J. Bedrick, Ronald M. Schrader
Open Textbooks
Lecture notes for Advanced Data Analysis (ADA1 Stat 427/527 and ADA2 Stat 428/528), Department of Mathematics and Statistics, University of New Mexico, Fall 2016-Spring 2017. Additional material including RMarkdown templates for in-class and homework exercises, datasets, R code, and video lectures are available on the course websites: https://statacumen.com/teaching/ada1 and https://statacumen.com/teaching/ada2 .
Contents
I ADA1: Software
- 0 Introduction to R, Rstudio, and ggplot
II ADA1: Summaries and displays, and one-, two-, and many-way tests of means
- 1 Summarizing and Displaying Data
- 2 Estimation in One-Sample Problems
- 3 Two-Sample Inferences
- 4 Checking Assumptions
- 5 One-Way Analysis of Variance
III ADA1: Nonparametric, categorical, …
Exploring New Models For Seatbelt Use In Survey Data, 2016 Old Dominion University
Exploring New Models For Seatbelt Use In Survey Data, Mark K. Ledbetter, Norou Diawara, Bryan E. Porter
Virginia Journal of Science
Problem: Several approaches to analyze seatbelt use have been proposed in the literature. Two methods that has not been explored are the use of unweighted and weighted logistic regression model and the use of item response theory (IRT) or the Rasch model. Since accurate methods to predict seatbelt use behavior based upon observed data must include a built-in design method and model, and overcome computation challenges, weighted and IRT method deem to be other options for an observational survey of seat belt use in the state of Virginia.
Method: The observed data from 136 sites within the Commonwealth …
Advances In Portmanteau Diagnostic Tests, 2016 The University of Western Ontario
Advances In Portmanteau Diagnostic Tests, Jinkun Xiao
Electronic Thesis and Dissertation Repository
Portmanteau test serves an important role in model diagnostics for Box-Jenkins Modelling procedures. A large number of Portmanteau test based on the autocorrelation function are proposed for a general purpose goodness-of-fit test. Since the asymptotic distributions for the statistics has a complicated form which makes it hard to obtain the p-value directly, the gamma approximation is introduced to obtain the p-value. But the approximation will inevitably introduce approximation errors and needs a large number of observations to yield a good approximation. To avoid some pitfalls in the approximation, the Lin-Mcleod Test is further proposed to obtain a numeric solution to …
Design Optimization Of A Stochastic Multi-Objective Problem: Gaussian Process Regressions For Objective Surrogates, 2016 Universidad de Los Andes - Colombia
Design Optimization Of A Stochastic Multi-Objective Problem: Gaussian Process Regressions For Objective Surrogates, Juan Sebastian Martinez, Piyush Pandita, Rohit K. Tripathy, Ilias Bilionis
The Summer Undergraduate Research Fellowship (SURF) Symposium
Multi-objective optimization (MOO) problems arise frequently in science and engineering situations. In an optimization problem, we want to find the set of input parameters that generate the set of optimal outputs, mathematically known as the Pareto frontier (PF). Solving the MOO problem is a challenge since expensive experiments can be performed only a constrained number of times and there is a limited set of data to work with, e.g. a roll-to-roll microwave plasma chemical vapor deposition (MPCVD) reactor for manufacturing high quality graphene. State-of-the-art techniques, e.g. evolutionary algorithms; particle swarm optimization, require a large amount of observations and do not …
Newsvendor Models With Monte Carlo Sampling, 2016 East Tennessee State University
Newsvendor Models With Monte Carlo Sampling, Ijeoma W. Ekwegh
Electronic Theses and Dissertations
Newsvendor Models with Monte Carlo Sampling by Ijeoma Winifred Ekwegh The newsvendor model is used in solving inventory problems in which demand is random. In this thesis, we will focus on a method of using Monte Carlo sampling to estimate the order quantity that will either maximizes revenue or minimizes cost given that demand is uncertain. Given data, the Monte Carlo approach will be used in sampling data over scenarios and also estimating the probability density function. A bootstrapping process yields an empirical distribution for the order quantity that will maximize the expected profit. Finally, this method will be used …
Spatio-Temporal Analysis Of Point Patterns, 2016 East Tennessee State University
Spatio-Temporal Analysis Of Point Patterns, Abdul-Nasah Soale
Electronic Theses and Dissertations
In this thesis, the basic tools of spatial statistics and time series analysis are applied to the case study of the earthquakes in a certain geographical region and time frame. Then some of the existing methods for joint analysis of time and space are described and applied. Finally, additional research questions about the spatial-temporal distribution of the earthquakes are posed and explored using statistical plots and models. The focus in the last section is in the relationship between number of events per year and maximum magnitude and its effect on how clustered the spatial distribution is and the relationship between …
Wind Climatology: A Study Of Trends On Rodgers' Dry Lakebed, 2016 University of Portland
Wind Climatology: A Study Of Trends On Rodgers' Dry Lakebed, Dana Coppernoll-Houston
STAR Program Research Presentations
A number of smaller projects at the Armstrong Flight Research Center fly on or close to the ground and are subject to ground-level winds. Many of these are new prototype models, such as PRANDTL-D (Preliminary Research Aerodynamic Design to Lower Drag). Waiting for the right conditions on a day of variable winds can sometimes mean that teams fail to complete testing. A strategic analysis of wind behavior at a locations where winds can vary greatly due to terrain could lend insight into the best times to test for near-ground aircraft. The purpose of this project was to data mine historical …
A Two-Strain Tb Model With Multiple Latent Stages, 2016 University of Tabriz
A Two-Strain Tb Model With Multiple Latent Stages, Azizeh Jabbari, Carlos Castillo-Chavez, Fereshteh Nazari, Baojun Song, Hossein Kheiri
Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works
A two-strain tuberculosis (TB) transmission model incorporating antibiotic-generated TB resistant strains and long and variable waiting periods within the latently infected class is introduced. The mathematical analysis is carried out when the waiting periods are modeled via parametrically friendly gamma distributions, a reasonable alternative to the use of exponential distributed waiting periods or to integral equations involving "arbitrary" distributions. The model supports a globally-asymptotically stable disease-free equilibrium when the reproduction number is less than one and an endemic equilibriums, shown to be locally asymptotically stable, or l.a.s., whenever the basic reproduction number is greater than one. Conditions for the existence …
Multilevel Models For Longitudinal Data, 2016 East Tennessee State University
Multilevel Models For Longitudinal Data, Aastha Khatiwada
Electronic Theses and Dissertations
Longitudinal data arise when individuals are measured several times during an ob- servation period and thus the data for each individual are not independent. There are several ways of analyzing longitudinal data when different treatments are com- pared. Multilevel models are used to analyze data that are clustered in some way. In this work, multilevel models are used to analyze longitudinal data from a case study. Results from other more commonly used methods are compared to multilevel models. Also, comparison in output between two software, SAS and R, is done. Finally a method consisting of fitting individual models for each …