Sökning: "sequential sampling methods"

Visar resultat 1 - 5 av 27 avhandlingar innehållade orden sequential sampling methods.

1. 1. On unequal probability sampling designs

   Författare :Anton Grafström; Lennart Bondesson; Sara De Luna; Imbi Traat; Umeå universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; conditional Poisson sampling; correlated Poisson sampling; entropy; extended Sampford sampling; Horvitz-Thompson estimator; inclusion probabilities; list-sequential sampling; non-rejective implementation; Pareto sampling; Poisson sampling; probability functions; ratio estimator; real-time sampling; repeated Poisson sampling; Sampford sampling; sampling designs; splitting method; unequal probability sampling; Mathematical statistics; Matematisk statistik; Mathematical Statistics; matematisk statistik;

   Sammanfattning : The main objective in sampling is to select a sample from a population in order to estimate some unknown population parameter, usually a total or a mean of some interesting variable. When the units in the population do not have the same probability of being included in a sample, it is called unequal probability sampling. LÄS MER

3. 2. On Methods for Real Time Sampling and Distributions in Sampling

   Författare :Kadri Meister; Daniel Thorburn; Umeå universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Mathematical statistics; Finite population sampling; inferential issues; real time sampling; sequential sampling methods; negative sampling correlations; model-design-based inference; multivariate Bernoulli and multinomial designs; Matematisk statistik; Mathematical statistics; Matematisk statistik; Mathematical Statistics; matematisk statistik;

   Sammanfattning : This thesis is composed of six papers, all dealing with the issue of sampling from a finite population. We consider two different topics: real time sampling and distributions in sampling. The main focus is on Papers A–C, where a somewhat special sampling situation referred to as real time sampling is studied. LÄS MER

4. 3. Unequal Probability Sampling in Active Learning and Traffic Safety

   Författare :Henrik Imberg; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; naturalistic driving; active learning; sampling weighing; optimal design; sequential sampling; probability sampling;

   Sammanfattning : This thesis addresses a problem arising in large and expensive experiments where incomplete data come in abundance but statistical analyses require collection of additional information, which is costly. Out of practical and economical considerations, it is necessary to restrict the analysis to a subset of the original database, which inevitably will cause a loss of valuable information; thus, choosing this subset in a manner that captures as much of the available information as possible is essential. LÄS MER

5. 4. Machine learning using approximate inference : Variational and sequential Monte Carlo methods

   Författare :Christian Andersson Naesseth; Thomas Schön; Fredrik Lindsten; Iain Murray; Linköpings universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY;

   Sammanfattning : Automatic decision making and pattern recognition under uncertainty are difficult tasks that are ubiquitous in our everyday life. The systems we design, and technology we develop, requires us to coherently represent and work with uncertainty in data. LÄS MER

7. 5. Metamodel-Based Multidisciplinary Design Optimization of Automotive Structures

   Författare :Ann-Britt Ryberg; Larsgunnar Nilsson; Anirban Basudhar; Linköpings universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; multidisciplinary design optimization MDO ; metamodel; artificial neural network ANN ; support vector machine SVM ; sequential sampling; crashworthiness; automotive structure; spot weld optimization;

   Sammanfattning : Multidisciplinary design optimization (MDO) can be used in computer aided engineering (CAE) to efficiently improve and balance performance of automotive structures. However, large-scale MDO is not yet generally integrated within automotive product development due to several challenges, of which excessive computing times is the most important one. LÄS MER