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Articles 31 - 37 of 37
Full-Text Articles in Statistical Models
Exponentially Weighted Moving Average Charts For Monitoring The Process Generalized Variance, Anna Khamitova
Exponentially Weighted Moving Average Charts For Monitoring The Process Generalized Variance, Anna Khamitova
College of Graduate Studies: Theses & Dissertations
The exponentially weighted moving average chart based on the sample generalized variance is studied under the independent multivariate normal model for the vector of quality measurements. The performance of the chart is based on an analysis of the chart's initial and steady-state run length distributions. The three methods that are commonly used to determinate run length distribution, simulation, the integral equation method, and the Markov chain approximation are discussed. The integral equation and Markov chain approaches are analytical methods that require a nu- merical method for determining the probability density and cumulative distribution functions describing the distribution of the sample …
Normal Mixture And Contaminated Model With Nuisance Parameter And Applications, Qian Fan
Normal Mixture And Contaminated Model With Nuisance Parameter And Applications, Qian Fan
Theses and Dissertations--Statistics
This paper intend to find the proper hypothesis and test statistic for testing existence of bilaterally contamination when there exists nuisance parameter. The test statistic is based on method of moments estimators. Union-Intersection test is used for testing if the distribution of population can be implemented by a bilaterally contaminated normal model with unknown variance. This paper also developed a hierarchical normal mixture model (HNM) and applied it to birth weight data. EM algorithm is employed for parameter estimation and a singular Bayesian information criterion (sBIC) is applied to choose the number components. We also proposed a singular flexible information …
Scalable Collaborative Filtering Recommendation Algorithms On Apache Spark, Walker Evan Casey
Scalable Collaborative Filtering Recommendation Algorithms On Apache Spark, Walker Evan Casey
CMC Senior Theses
Collaborative filtering based recommender systems use information about a user's preferences to make personalized predictions about content, such as topics, people, or products, that they might find relevant. As the volume of accessible information and active users on the Internet continues to grow, it becomes increasingly difficult to compute recommendations quickly and accurately over a large dataset. In this study, we will introduce an algorithmic framework built on top of Apache Spark for parallel computation of the neighborhood-based collaborative filtering problem, which allows the algorithm to scale linearly with a growing number of users. We also investigate several different variants …
An Investigation Of Sensitivity Of An F Test In Locating Change Points In Linear Regression, Jing Sun
An Investigation Of Sensitivity Of An F Test In Locating Change Points In Linear Regression, Jing Sun
College of Graduate Studies: Theses & Dissertations
Change point is a statistic phenomenon, which has many direct applications in climatology, bioinformatics, finance, oceanography and medical imaging. In this thesis, we investigate the sensitivity of the F-test for detecting change points in linear regression, using a two-phase linear regression model. it offers an effective method to detect "undocumented" change points using a form of an F-test. Using simulated data, we explore its sensitivity and accuracy with respect t different parameters in the model.
A Bayesian Model Of Fertility Decisions In Relationship To Female Labor Force Participation, Rebecca C. Wardrop
A Bayesian Model Of Fertility Decisions In Relationship To Female Labor Force Participation, Rebecca C. Wardrop
Senior Independent Study Theses
Due to the increasing number of women in the labor force, opportunity costs associated with labor force participation are becoming an important factor in fertility decisions. Further, these decisions are assumed to be dynamic as the opportunity costs change as a woman progresses through her career. A Bayesian statistical model , which allows the distribution of the likelihood of having children to be updated as information is gathered, lends itself to the dynamicity of the decision-making process. A generalized model for fertility decisions in terms of labor force participation is created. I also discuss potentials for implementation and furthering the …
Modelling And Analysis On Noisy Financial Time Series, Jinsong Leng
Modelling And Analysis On Noisy Financial Time Series, Jinsong Leng
Research outputs 2014 to 2021
Building the prediction model(s) from the historical time series has attracted many researchers in last few decades. For example, the traders of hedge funds and experts in agriculture are demanding the precise models to make the prediction of the possible trends and cycles. Even though many statistical or machine learning (ML) models have been proposed, however, there are no universal solutions available to resolve such particular prob-lem. In this paper, the powerful forward-backward non-linear filter and wavelet-based denoising method are introduced to remove the high level of noise embedded in financial time series. With the filtered time series, the statistical …
Hierarchical Graphical Bayesian Models In Psychology, Guillermo Campitelli, Guillermo Macbeth
Hierarchical Graphical Bayesian Models In Psychology, Guillermo Campitelli, Guillermo Macbeth
Research outputs 2014 to 2021
The improvement of graphical methods in psychological research can promote their use and a better comprehension of their expressive power. The application of hierarchical Bayesian graphical models has recently become more frequent in psychological research. The aim of this contribution is to introduce suggestions for the improvement of hierarchical Bayesian graphical models in psychology. This novel set of suggestions stems from the description and comparison between two main approaches concerned with the use of plate notation and distribution pictograms. It is concluded that the combination of relevant aspects of both models might improve the use of powerful hierarchical Bayesian graphical …