Sökning: "Hodrick-Prescott filter"

Hittade 3 avhandlingar innehållade orden Hodrick-Prescott filter.

  1. 1. Functional Hodrick-Prescott Filter

    Detta är en avhandling från Linnaeus University

    Författare :Hiba Nassar; Astrid Hilbert; Alexander Meister; [2013]
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Inverse problems; adaptive estimation; Hodrick-Prescott filter; smoothing; trend extraction; Gaussian measures on a Hilbert space.; Mathematics; Matematik;

    Sammanfattning : The study of functional data analysis is motivated by their applications in various fields of statistical estimation and statistical inverse problems.In this thesis we propose a functional Hodrick-Prescott filter. This filter is applied to functional data which take values in an infinite dimensional separable Hilbert space. LÄS MER

  2. 2. The Hodrick-Prescott Filter: Functional aspects and statistical estimation

    Detta är en avhandling från Växjö : Linnaeus University Press

    Författare :Hiba Nassar; Astrid Hilbert; James Ramsay; [2015]
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Hodrick-Prescott Filter; Functional data; Estimation; Smoothing Operator.; Tillämpad matematik; Applied Mathematics;

    Sammanfattning : .... LÄS MER

  3. 3. Some Contributions to Filtering, Modeling and Forecasting of Heteroscedastic Time Series

    Detta är en avhandling från Stockholm : Department of Statistics, Stockholm University

    Författare :Pär Stockhammar; Lars-Erik Öller; Daniel Thorburn; Agustin Maravall; [2010]
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Heteroscedasticity; variance stabilizing filters; the mixed Normal - Asymmetric Laplace distribution; density forecasting; detrending filters; spectral analysis; the connection between financial data and economic growth; SOCIAL SCIENCES Statistics; computer and systems science Statistics; SAMHÄLLSVETENSKAP Statistik; data- och systemvetenskap Statistik; statistik; Statistics;

    Sammanfattning : Heteroscedasticity (or time-dependent volatility) in economic and financial time series has been recognized for decades. Still, heteroscedasticity is surprisingly often neglected by practitioners and researchers. This may lead to inefficient procedures. LÄS MER