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- Bilaterally contaminated normal model (1)
- Contaminated Chi-Square Model (1)
- Contamination Beta mixture model (1)
- EM Algorithm (1)
- Feature selection (1)
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- Finite Mixture Models (1)
- Finite mixture model (1)
- Gene expression (1)
- Genes (1)
- Hierarchical Mixture Model (1)
- Hierarchical normal mixture model (1)
- Homogeneity Test (1)
- In- formation Criterion (1)
- Longitudinal data (1)
- MLRT (1)
- Micro-array Analysis (1)
- Micro-array data analysis (1)
- Microarray (1)
- Mixture Model (1)
- Model selection (1)
- Modified log-likelihood ratio test (1)
- Sign averages (1)
- Singular Bayesian information criterion (1)
- Singular flexible information criterion (1)
- UnionIntersection test (1)
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Articles 1 - 5 of 5
Full-Text Articles in Microarrays
Beta Mixture And Contaminated Model With Constraints And Application With Micro-Array Data, Ya Qi
Beta Mixture And Contaminated Model With Constraints And Application With Micro-Array Data, Ya Qi
Theses and Dissertations--Statistics
This dissertation research is concentrated on the Contaminated Beta(CB) model and its application in micro-array data analysis. Modified Likelihood Ratio Test (MLRT) introduced by [Chen et al., 2001] is used for testing the omnibus null hypothesis of no contamination of Beta(1,1)([Dai and Charnigo, 2008]). We design constraints for two-component CB model, which put the mode toward the left end of the distribution to reflect the abundance of small p-values of micro-array data, to increase the test power. A three-component CB model might be useful when distinguishing high differentially expressed genes and moderate differentially expressed genes. If the null hypothesis above …
Feature Selection For Longitudinal Data By Using Sign Averages To Summarize Gene Expression Values Over Time, Suyan Tian, Chi Wang
Feature Selection For Longitudinal Data By Using Sign Averages To Summarize Gene Expression Values Over Time, Suyan Tian, Chi Wang
Biostatistics Faculty Publications
With the rapid evolution of high-throughput technologies, time series/longitudinal high-throughput experiments have become possible and affordable. However, the development of statistical methods dealing with gene expression profiles across time points has not kept up with the explosion of such data. The feature selection process is of critical importance for longitudinal microarray data. In this study, we proposed aggregating a gene’s expression values across time into a single value using the sign average method, thereby degrading a longitudinal feature selection process into a classic one. Regularized logistic regression models with pseudogenes (i.e., the sign average of genes across time as predictors) …
Development In Normal Mixture And Mixture Of Experts Modeling, Meng Qi
Development In Normal Mixture And Mixture Of Experts Modeling, Meng Qi
Theses and Dissertations--Statistics
In this dissertation, first we consider the problem of testing homogeneity and order in a contaminated normal model, when the data is correlated under some known covariance structure. To address this problem, we developed a moment based homogeneity and order test, and design weights for test statistics to increase power for homogeneity test. We applied our test to microarray about Down’s syndrome. This dissertation also studies a singular Bayesian information criterion (sBIC) for a bivariate hierarchical mixture model with varying weights, and develops a new data dependent information criterion (sFLIC).We apply our model and criteria to birth- weight and gestational …
Contaminated Chi-Square Modeling And Its Application In Microarray Data Analysis, Feng Zhou
Contaminated Chi-Square Modeling And Its Application In Microarray Data Analysis, Feng Zhou
Theses and Dissertations--Statistics
Mixture modeling has numerous applications. One particular interest is microarray data analysis. My dissertation research is focused on the Contaminated Chi-Square (CCS) Modeling and its application in microarray. A moment-based method and two likelihood-based methods including Modified Likelihood Ratio Test (MLRT) and Expectation-Maximization (EM) Test are developed for testing the omnibus null hypothesis of no contamination of a central chi-square distribution by a non-central Chi-Square distribution. When the omnibus null hypothesis is rejected, we further developed the moment-based test and the EM test for testing an extra component to the Contaminated Chi-Square (CCS+EC) Model. The moment-based approach is easy and …
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 …