Search for dissertations about: "sample estimate"
Showing result 1 - 5 of 281 swedish dissertations containing the words sample estimate.
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1. Quantization of Random Processes and Related Statistical Problems
Abstract : In this thesis we study a scalar uniform and non-uniform quantization of random processes (or signals) in average case setting. Quantization (or discretization) of a signal is a standard task in all nalog/digital devices (e.g., digital recorders, remote sensors etc. READ MORE
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2. Investigating the parameters that influence the behaviour of natural iron ores during the iron production process
Abstract : In the iron production processes, sinters and pellets are mostly used as raw materials due to their consistency with respect to physical and chemical properties. However, natural iron ores, as mined, are rarely used directly as a feed material for iron processing. READ MORE
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3. Deriving landscape metrics from sample data
Abstract : This thesis focuses on the efficiency of using sampling methods to derive landscape metrics. It also explores what sampling methods are to be preferred for different metrics and how metrics in some cases can be redefined to better suit a sample-based data collection framework. READ MORE
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4. Estimating Interviewer Effects in Sample Surveys : Some Contributions
Abstract : This thesis focuses on measurement errors that could be ascribed to the interviewers. To study interviewer variability a measurement error model is formulated which makes a clear distinction between three sources of randomness: the sample selection, interviewer assignment, and interviewing. READ MORE
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5. Comparative network analysis of human cancer: sparse graphical models with modular constraints and sample size correction
Abstract : In the study of transcriptional data for different groups (e.g. cancer types) it's reasonable to assume that some dependencies between genes on a transcriptional or genetic variants level are common across groups. Also, that this property is preserved locally, thus defining a modular structure in the model networks. READ MORE