Mostrando recursos 1 - 6 de 6

  1. Modelling human immunodeficiency virus ribonucleic acid levels with finite mixtures for censored longitudinal data

    Grün, Bettina; Hornik, Kurt
    The measurement of human immunodeficiency virus ribonucleic acid levels over time leads to censored longitudinal data. Suitable models for dynamic modelling of these levels need to take this data characteristic into account. If groups of patients with different developments of the levels over time are suspected the model class of finite mixtures of mixed effects models with censored data is required.We describe the model specification and derive the estimation with a suitable expectation-maximization algorithm.We propose a convenient implementation using closed form formulae for the expected mean and variance of the truncated multivariate distribution. Only efficient evaluation of the cumulative multivariate normal distribution function is required. Model selection as...

  2. Modelling human immunodeficiency virus ribonucleic acid levels with finite mixtures for censored longitudinal data

    Grün, Bettina; Hornik, Kurt
    The measurement of human immunodeficiency virus ribonucleic acid levels over time leads to censored longitudinal data. Suitable models for dynamic modelling of these levels need to take this data characteristic into account. If groups of patients with different developments of the levels over time are suspected the model class of finite mixtures of mixed effects models with censored data is required.We describe the model specification and derive the estimation with a suitable expectation-maximization algorithm.We propose a convenient implementation using closed form formulae for the expected mean and variance of the truncated multivariate distribution. Only efficient evaluation of the cumulative multivariate normal distribution function is required. Model selection as...

  3. The determinants of merger waves: An international perspective

    Gugler, Klaus; Mueller, Dennis C.; Weichselbaumer, Michael
    One of the most conspicuous features of mergers is that they come in waves that are correlated with increases in share prices and price/earnings ratios. We use a natural way to discriminate between pure stock market influences on firm decisions and other influences by examining merger patterns for both listed and unlisted firms. If "real" changes in the economy drive merger waves, as some neoclassical theories of mergers predict, both listed and unlisted firms should experience waves. We find significant differences between listed and unlisted firms as predicted by behavioral theories of merger waves. (author's abstract)

  4. Die Entwicklungsgeschichte einer BürgerENERGIEgenossenschaft. Solargenossenschaft Rosenheim

    Reiner, Elisabeth
    (kein Abstract vorhanden)

  5. Model Uncertainty and Aggregated Default Probabilities: New Evidence from Austria

    Hofmarcher, Paul; Kerbl, Stefan; Grün, Bettina; Sigmund, Michael; Hornik, Kurt
    Understanding the determinants of aggregated default probabilities (PDs) has attracted substantial research over the past decades. This study addresses two major difficulties in understanding the determinants of aggregate PDs: Model uncertainty and multicollinearity among the regressors. We present Bayesian Model Averaging (BMA) as a powerful tool that overcomes model uncertainty. Furthermore, we supplement BMA with ridge regression to mitigate multicollinearity. We apply our approach to an Austrian dataset. Our findings suggest that factor prices like short term interest rates and energy prices constitute major drivers of default rates, while firms' profits reduce the expected number of failures. Finally, we show that the results of our baseline model are fairly robust to the choice...

  6. Model Uncertainty and Aggregated Default Probabilities: New Evidence from Austria

    Hofmarcher, Paul; Kerbl, Stefan; Grün, Bettina; Sigmund, Michael; Hornik, Kurt
    Understanding the determinants of aggregated default probabilities (PDs) has attracted substantial research over the past decades. This study addresses two major difficulties in understanding the determinants of aggregate PDs: Model uncertainty and multicollinearity among the regressors. We present Bayesian Model Averaging (BMA) as a powerful tool that overcomes model uncertainty. Furthermore, we supplement BMA with ridge regression to mitigate multicollinearity. We apply our approach to an Austrian dataset. Our findings suggest that factor prices like short term interest rates and energy prices constitute major drivers of default rates, while firms' profits reduce the expected number of failures. Finally, we show that the results of our baseline model are fairly robust to the choice...

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