Results 11 to 20 of about 114,749 (302)
Stochastic mortality models seek to forecast future mortality rates; thus, it is apparent that the objective variable should be the mortality rate expressed in the original scale. However, the performance of stochastic mortality models—in terms, that is,
Miguel Santolino
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The ongoing pandemic has resulted in the development of models dealing with the rate of virus spread and the modelling of mortality rates μx,t. A new method of modelling the mortality rates μx,t with different time intervals of higher and lower ...
Piotr Sliwka, Leslaw Socha
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Identification and Forecasting in Mortality Models [PDF]
Mortality models often have inbuilt identification issues challenging the statistician. The statistician can choose to work with well-defined freely varying parameters, derived as maximal invariants in this paper, or with ad hoc identified parameters which at first glance seem more intuitive, but which can introduce a number of unnecessary challenges ...
Bent Nielsen, Jens P. Nielsen
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This work proposes a backtesting analysis that compares the Lee–Carter and the Cairns–Blake–Dowd mortality models, employing Italian data. The mortality data come from the Italian National Statistics Institute (ISTAT) database and span the period 1975 ...
Carlo Maccheroni, Samuel Nocito
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Predicting the outcome of myocardial infarction in elderly and senile patients with type 2 diabetes
Diabetes mellitus (DM) is a relevant problem today. The extremely high prevalence, progressive course, multiple severe, sometimes disabling, complications, premature mortality, heavy financial burden - this is an incomplete list of the socio-economic ...
A. L. Terekhova +3 more
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COVID-19: How to make between-country comparisons
Background: Different countries have adopted different containment and testing strategies for SARS-CoV-2. The difference in testing makes it difficult to compare the effect of different containment strategies.
Rutger A. Middelburg, Frits R. Rosendaal
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Bayesian Poisson Log-Bilinear Mortality Projections [PDF]
Mortality projections are major concerns for public policy, social security and private insurance. This paper implements a Bayesian log-bilinear Poisson regression model to forecast mortality.
Czado, Claudia, Delwarde, A., Denuit, M.
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Advances in mortality forecasting: introduction [PDF]
Mortality forecasts are essential for predicting the future extent of population ageing, and for determining the sustainability of pension schemes and social security systems. They are also useful in setting life insurance premiums, and in helping governments plan for the changing needs of their societies for health care and other services (European ...
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Evaluation of simple methods for regional mortality forecasts
Background In recent decades, considerable research effort has been dedicated to improving mortality forecasting methods. While making valuable contributions to the literature, the bulk of this research has focused on national populations—yet much ...
Tom Wilson
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Coherent forecasts of mortality with compositional data analysis
Background: Mortality trends for subpopulations, e.g., countries in a region or provinces in a country, tend to change similarly over time. However, when forecasting subpopulations independently, the forecast mortality trends often diverge.
Marie-Pier Bergeron-Boucher +3 more
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