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variables compared to standard, univariate, forecasting methods. We evaluate the impact of using combined information in the …
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While previous academic research highlights the potential of machine learning and big data for predicting corporate bond recovery rates, the operations management challenge is to identify the relevant predictive variables and the appropriate model. In this paper, we use meta-learning to combine...
Persistent link: https://www.econbiz.de/10013363030
understanding mortality risk and longevity risk. Studies of mortality forecasting are of interest among actuaries and demographers … because mortality forecasting can quantify mortality and longevity risks. There is an abundance of literature on the topic of … modelling and forecasting mortality, which often leads to confusion in determining a particular model to be adopted as a …
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We propose a new approach for estimating the state-level direct and indirect economic cost of obesity in the United States for the time period 1996 to 2018. Our unique top-down methodology integrates a prevalence-based method with various medical-level costs, economic, demographic, and...
Persistent link: https://www.econbiz.de/10013556731
, infrastructure development and conducive business environments need to be developed. For that, accurate forecasting of international … purpose of this study is to develop accurate forecasting models for total international arrivals in Sri Lanka and its top 10 … forecasting is necessary for tourism strategies and planning, and (c) the SARIMA method provides accurate forecasts in the …
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, researchers around the world are constantly developing new forecasting models to successfully predict the unemployment rate. This … article presents a new model that combines two deep learning methodologies used for time series forecasting to find the future …
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