Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 943 for “"Statistical methods."”.
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Statistical methods for spatial screening
… very expensive and time-consuming. This demands statistical tools to provide more effective sampling strategy and to characterize the UXO distribution. Based on the physical characteristics of UXO deposition, we adopt a simplified Neyman-Scott process to model the UXO distribution. A line …
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Statistical methods for random rotations
… location model for orientation data is simple, statistical methods for estimation and inference for the location parameter, S are limited. In this dissertation we develop point estimation and confidence region methods for the central orientation.</p> <p>Both extrinsic and intrinsic approaches to …
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Statistical methods for bullet matching
… questioning the scientific validity of these methods. Further criticisms were made in a 2016 report by the President's Council of Advisors on Science and Technology (PCAST). After PCAST determined that there has only been one appropriately designed study to assess the accuracy of bullet …
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Topic detection through statistical methods
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.
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Statistical methods of earthquake attenuation
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Civil Engineering, 1987
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Statistical methods for multivariate meta-analysis
… exposure misclassification, and meta-regression methods adjusting for post-randomization variables. In studies evaluating the accuracy of diagnostic tests, three designs are commonly used, crossover, randomized, and non-comparative. Existing methods for meta-analysis of diagnostic tests mainly …
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Statistical Methods for Large Complex Datasets
… century. This thesis aims at developing novel statistical methods that can efficiently analyze a variety of large complex datasets. Underlying the umbrella theme of big data modeling, we present statistical methods for two different classes of large complex datasets. The first half of the …
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Statistical methods for fMRI data analysis
… of fMRI data pose some challenges to traditional statistical methods which focus on data with smal sample size and simple data structure. The functional activation detection and functional connectivity network analysis by using fMRI are two important research topics in the neuroscience. In this …
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Statistical methods for learning sparse features
With the fast development of networking, data storage, and the data collection capacity, big data are now rapidly expanding in all science and engineering domains. When dealing with such data, it is appealing if we can extract the hidden sparse structure of the data since sparse structures allow us …
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Statistical Methods for Off-Policy Learning
… in inappropriate causal assumptions and statistically inefficient estimation procedures. This has limited the wider application of off-policy learning to many real-world problems. Motivated by the dynamic pricing problem encountered in container logistics, this thesis takes steps towards …
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Computational statistical methods in chemical engineering
… problems. This thesis covers applications of statistical learning spanning a range of relative importance of data versus existing detailed theory. In each application, the quantity and quality of data available from experimental systems are used in conjunction with an understanding of the …
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Statistical methods to infer biological interactions
… raw data, increasing the need for computational methods to disentangle true interactions from noise. In this thesis, we focus on statistical methods to infer two classes of important biological interactions: protein-protein interactions and the link between genotypes and phenotypes. In the first …
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Statistical methods in ultrasonic tissue characterization
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.
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Statistical Methods for Out-of-distribution Detection
… data characteristics and data correlations that statistical methods can model. Accordingly, this thesis attempts to incorporate statistical methods into deep neural networks to improve the OOD sensitivity. Specifically, this thesis proposes four novel methods to address these issues. The main …
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Statistical methods for genetics and genomics studies
… assessment of RNA quality is essential. Existing methods for estimating the quality of RNA on microarray either suffer from subjectivity or are inefficient in performance. To overcome these drawbacks, in this dissertation, a linear regression method for assessing RNA quality for a hybridized …
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Statistical Methods for Biological and Relational Data
Methods for biological and relational data have pose challenges for statistical modeling. For biological data, gene expression data have high-dimensionality, and T-cell receptor (TCR) data under-sample receptor populations. For relational data, there are dependencies among the observations. This …
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Statistical methods for weather-related insurance claims
… Several aspects have to be considered in the statistical modelling of this relationship. For instance, some regions in the world are more used to severe rainfall events than others and, hence, presumably less vulnerable to small amounts of rainfall than others. Spatial statistics provides a …
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Statistical methods for supporting urgent care delivery
… and server performance was investigated. Initial methods included linear regression to predict calls per day into a call centre, loess to predict arrival rates, and moving averages to deal with unexpected flu pandemics. We also tried to understand the behaviour of GPs and develop a fair rating …
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Statistical methods for indirectly observed network data
… space model for ARD. This dissertation proposes statistical methods for methods for estimating social network and population characteristics using one type of social network data collected using standard surveys. First, a method to estimate both individual social network size (i.e., degree) and …
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Statistical methods for binomial and Gaussian sequences
We propose new methods and frameworks for approaching three different statistical sequence problems. The first is a tree-based computational method for calculating the Poisson Binomial distribution function, which is the distribution of a sum of independent but not identically distributed Bernoulli …
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