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Akademický článek

Would You Take an Open-Label Placebo Pill or Give One to Your Child? Findings from a Cross-Sectional Survey

Autor: Schienle A, Seibel A

Publikováno v: Psychology Research and Behavior Management, Vol Volume 17, Pp 393-400 (2024)

Anne Schienle, Arved Seibel Department of Clinical Psychology, University of Graz, Graz, AustriaCorrespondence: Anne Schienle, Email anne.schienle@uni-graz.atBackground: Open-label placebos (OLPs), honestly prescribed regarding their inert nature, ha

Externí odkaz: https://doaj.org/article/97bcf30d23584b999c0f06d6f116300f

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Akademický článek

Combined Cognitive-Behavioral Therapy and Placebo Treatment for Patients with Depression: A Follow-Up Assessment

Autor: Schienle A, Jurinec N

Publikováno v: Psychology Research and Behavior Management, Vol Volume 14, Pp 233-238 (2021)

Anne Schienle,1 Nina Jurinec1,2 1 Instiute of Psychology, University of Graz, Graz, Austria; 2Community Health Center Gornja Radgona, Gornja Radgona, SloveniaCorrespondence: Anne Schienle Instiute of Psychology, University of Graz, Universitätsplatz

Externí odkaz: https://doaj.org/article/a3d916dd90cc4b87bf7d86be26bc2366

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Simple Macroeconomic Forecast Distributions for the G7 Economies

Autor: Becker, Friederike, Krüger, Fabian, Schienle, Melanie

We present a simple method for predicting the distribution of output growth and inflation in the G7 economies. The method is based on point forecasts published by the International Monetary Fund (IMF), as well as robust statistics from the empirical

Externí odkaz: http://arxiv.org/abs/2408.08304

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Estimation of spatio-temporal extremes via generative neural networks

Autor: Bülte, Christopher, Leimenstoll, Lisa, Schienle, Melanie

Recent methods in modeling spatial extreme events have focused on utilizing parametric max-stable processes and their underlying dependence structure. In this work, we provide a unified approach for analyzing spatial extremes with little available da

Externí odkaz: http://arxiv.org/abs/2407.08668

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Direction Augmentation in the Evaluation of Armed Conflict Predictions

Autor: Bracher, Johannes, Rüter, Lotta, Krüger, Fabian, Lerch, Sebastian, Schienle, Melanie

In many forecasting settings, there is a specific interest in predicting the sign of an outcome variable correctly in addition to its magnitude. For instance, when forecasting armed conflicts, positive and negative log-changes in monthly fatalities r

Externí odkaz: http://arxiv.org/abs/2304.12108

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Robust Knockoffs for Controlling False Discoveries With an Application to Bond Recovery Rates

Autor: Görgen, Konstantin, Nazemi, Abdolreza, Schienle, Melanie

We address challenges in variable selection with highly correlated data that are frequently present in finance, economics, but also in complex natural systems as e.g. weather. We develop a robustified version of the knockoff framework, which addresse

Externí odkaz: http://arxiv.org/abs/2206.06026

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Predicting Value at Risk for Cryptocurrencies With Generalized Random Forests

Autor: Buse, Rebekka, Görgen, Konstantin, Schienle, Melanie

We study the prediction of Value at Risk (VaR) for cryptocurrencies. In contrast to classic assets, returns of cryptocurrencies are often highly volatile and characterized by large fluctuations around single events. Analyzing a comprehensive set of 1

Externí odkaz: http://arxiv.org/abs/2203.08224

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