Sökning: "non probability sampling"

Visar resultat 1 - 5 av 50 avhandlingar innehållade orden non probability sampling.

  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. Markov Chains, Renewal, Branching and Coalescent Processes : Four Topics in Probability Theory

    Författare :Andreas Nordvall Lagerås; Thomas Höglund; Ingemar Kaj; Stockholms universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Mathematical statistics; Matematisk statistik; matematisk statistik; Mathematical Statistics;

    Sammanfattning : This thesis consists of four papers.In paper 1, we prove central limit theorems for Markov chains under (local) contraction conditions. As a corollary we obtain a central limit theorem for Markov chains associated with iterated function systems with contractive maps and place-dependent Dini-continuous probabilities. LÄS MER

  4. 3. Statistical modeling in international large-scale assessments

    Författare :Inga Laukaityte; Marie Wiberg; Kenny Bränberg; Ewa Rolfsman; Bernard Veldkamp; Umeå universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; multilevel model; plausible values; sampling weights; missing information; multiple imputation; non-monotone missing pattern; TIMSS; PISA; Statistics; statistik; pedagogik; Education;

    Sammanfattning : This thesis contributes to the area of research based on large-scale educational assessments, focusing on the application of multilevel models. The role of sampling weights, plausible values (response variable imputed multiple times) and imputation methods are demonstrated by simulations and applications to TIMSS (Trends in International Mathematics and Science Study) and PISA (Programme for International Student Assessment) data. LÄS MER

  5. 4. Learning Stochastic Nonlinear Dynamical Systems Using Non-stationary Linear Predictors

    Författare :Mohamed Abdalmoaty; Håkan Hjalmarsson; Jimmy Olsson; KTH; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Stochastic Nonlinear Systems; Nonlinear System Identification; Learning Dynamical Models; Maximum Likelihood; Estimation; Process Disturbance; Prediction Error Method; Non-stationary Linear Predictors; Intractable Likelihood; Latent Variable Models; Electrical Engineering; Elektro- och systemteknik;

    Sammanfattning : The estimation problem of stochastic nonlinear parametric models is recognized to be very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the maximum likelihood estimator and the optimal mean-square error predictor using Monte Carlo methods. LÄS MER

  7. 5. Offline and Online Models for Learning Pairwise Relations in Data

    Författare :Fazeleh Sadat Hoseini; Chalmers tekniska högskola; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Mulit-Armed Bandit; Pairwise Relations; Performance Modeling; Motion Trajectory Clustering; Minimax Distance; Bottleneck Identification; Online Learning; Representation Learning; Memory Efficiency; Concurrent Programming; Thompson Sampling;

    Sammanfattning : Pairwise relations between data points are essential for numerous machine learning algorithms. Many representation learning methods consider pairwise relations to identify the latent features and patterns in the data. This thesis, investigates learning of pairwise relations from two different perspectives: offline learning and online learning. LÄS MER