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  1. Bayes estimates of multimodal density features using DNA and Economic Data
    Autor*in: Basturk, Nalan; Hoogerheide, Lennart; Dijk, Herman K. van
    Erschienen: [2021]
    Verlag:  Tinbergen Institute, Amsterdam, The Netherlands

    In several scientific fields, like bioinformatics, financial and macro-economics, important theoretical and practical issues exist that involve multimodal data distributions. We propose a Bayesian approach using mixtures distributions to approximate... mehr

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    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 432
    Fernleihe:
    keine Fernleihe

     

    In several scientific fields, like bioinformatics, financial and macro-economics, important theoretical and practical issues exist that involve multimodal data distributions. We propose a Bayesian approach using mixtures distributions to approximate accurately such data distributions. Shape and other features of the mixture approximations are estimated including their uncertainty. For discrete data, we introduce a novel mixture of shifted Poisson distributions with an unknown number of components, which overcomes the equidispersion restriction in the standard Poisson which accomodates a wide range of shapes such as multimodality and long tails. Our simulation-based Bayesian inference treats the density features as random variables and highest credibility regions around features are easily obtained. For discrete data we develop an adapted version of the Reversible Jump Markov Chain Monte Carlo (RJMCMC) method, which allows for an unknown number of components instead of the more restrictive approach of choosing a particular number of mixture components using information criteria. Using simulated data, we show that our approach works successfully for three issues that one encounters during the estimation of mixtures: label switching; mixture complexity and prior information and mode membership versus component membership. The proposed method is applied to three empirical data sets: The count data method yields a novel perspective of the data on DNA tandem repeats in Schaap et al. (2013); the bimodal distribution of payment details of clients obtaining a loan from a financial institution in Spain in 1990 gives insight into the repayment ability of individual clients; and the distribution of the modes of real GDP growth data from the PennWorld Tables and their evolution over time explores possible world-wide economic convergence as well as group convergence between the US and European countries. The results of our descriptive analysis may be used as input for forecasting and policy analysis.

     
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/237750
    Schriftenreihe: Array ; TI 2021, 017
    Schlagworte: Multimodality; mixtures; Markov Chain Monte Carlo; Bayesian Inference
    Umfang: 1 Online-Ressource (circa 33 Seiten), Illustrationen
  2. Bayesian mode inference for discrete distributions in economics and finance
    Autor*in: Cross, Jamie; Hoogerheide, Lennart; Labonne, Paul; Dijk, Herman K. van
    Erschienen: [2023]
    Verlag:  Tinbergen Institute, Amsterdam, The Netherlands

    Detecting heterogeneity within a population is crucial in many economic and financial applications. Econometrically, this requires a credible determination of multimodality in a given data distribution. We propose a straightforward yet effective... mehr

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    Verlag (kostenfrei)
    Verlag (kostenfrei)
    Resolving-System (kostenfrei)

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 432
    Fernleihe:
    keine Fernleihe

     

    Detecting heterogeneity within a population is crucial in many economic and financial applications. Econometrically, this requires a credible determination of multimodality in a given data distribution. We propose a straightforward yet effective technique for mode inference in discrete data distributions which involves fitting a mixture of novel shifted-Poisson distributions. The credibility and utility of our proposed approach is demonstrated through empirical investigations on datasets pertaining to loan default risk and inflation expectations.

     
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/273849
    Schriftenreihe: Array ; TI 2023, 038
    Schlagworte: Bayesian Inference; Mixture Models; Mode Inference; Multimodality; Shifted-Poisson
    Umfang: 1 Online-Ressource (circa 11 Seiten), Illustrationen
  3. Bayesian mode inference for discrete distributions in economics and finance
    Autor*in: Cross, Jamie; Hoogerheide, Lennart; Labonne, Paul; Dijk, Herman K. van
    Erschienen: 2023
    Verlag:  BI Norwegian Business School, Centre for Applied Macro-Petroleum economics (CAMP), Oslo

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    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    VS 321
    Fernleihe:
    keine Fernleihe
    Export in Literaturverwaltung   RIS-Format
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 11250/3095578
    Schriftenreihe: CAMP working paper series ; no. 2023, 11
    Schlagworte: Bayesian Inference; Mixture Models; Mode Inference; Multimodality; Shifted-Poisson
    Umfang: 1 Online-Ressource (circa 11 Seiten)
  4. Bayesian (non-)unique sparse factor modelling
    Autor*in: Kaufmann, Sylvia; Pape, Markus
    Erschienen: [2023]
    Verlag:  [Study Center Gerzensee], [Gerzensee]

    Factor modelling extracts common information from a high-dimensional data set into few common components, where the latent factors usually explain a large share of data variation. Exploratory factor estimation induces sparsity into the loading matrix... mehr

    Zugang:
    Verlag (kostenfrei)
    Resolving-System (kostenfrei)

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 529
    Fernleihe:
    keine Fernleihe

     

    Factor modelling extracts common information from a high-dimensional data set into few common components, where the latent factors usually explain a large share of data variation. Exploratory factor estimation induces sparsity into the loading matrix to associate units or series with those factors most strongly associated with them, eventually determining factor interpretation. We motivate geometrically under which circumstances it may be necessary to consider the existence of multiple sparse factor loading matrices with similar degrees of sparsity for a given data set. We propose two MCMC approaches for Bayesian inference and corresponding post-processing algorithms to uncover multiple sparse representations of the factor loadings matrix. We investigate both approaches in a simulation study. Applied to data on country-specific gross domestic product and U.S. price components series, we retrieve multiple sparse factor representations for each data set. Both approaches prove useful to discriminate between pervasive and weaker factors.

     
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/283524
    Schriftenreihe: Working paper / Study Center Gerzensee ; 23, 04
    Schlagworte: Multimodality; Sparsity; Pervasive and weak factors
    Umfang: 1 Online-Ressource (circa 49 Seiten), Illustrationen
  5. Legitime Sprachen, legitime Identitäten: Interaktionsanalysen im spätmodernen "Deutsch als Fremdsprache"-Klassenzimmer
    Autor*in: Rellstab, Daniel H.
    Erschienen: 2023
    Verlag:  transcript Verlag ; DEU ; Bielefeld

    Das Einüben der Fähigkeit, mit sprachlicher und kultureller Vielfalt produktiv umzugehen, ist ein Kernanliegen des zeitgemäßen Fremdsprachenunterrichts. Doch wie ist der Umgang mit dieser im Klassenzimmer organisiert? Daniel H. Rellstab analysiert... mehr

     

    Das Einüben der Fähigkeit, mit sprachlicher und kultureller Vielfalt produktiv umzugehen, ist ein Kernanliegen des zeitgemäßen Fremdsprachenunterrichts. Doch wie ist der Umgang mit dieser im Klassenzimmer organisiert? Daniel H. Rellstab analysiert auf der Basis eines von Erving Goffman geprägten Interaktionsverständnisses Interaktionen in "Deutsch als Fremdsprache"-Klassenzimmern. Dabei zeigt er, welche Ressourcen Lehrkräfte sowie Schülerinnen und Schüler in der Interaktion einsetzen, wie sie aushandeln, welche Sprachen legitim, welche illegitim sind, und wie sie dabei Identitäten und Normen re- und dekonstruieren.

     
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