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🔗 Source: robjhyndman.com
📊 Size: 599 KB
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Prospective life tables depend on forecasting age-specific mortality, with various extrapolative methods available, including the Lee-Carter method, Bayesian modeling, generalized linear modeling, and state-space approaches. This chapter covers extrapolative methods for forecasting age-specific central death rates and deriving stochastic life expectancy forecasts based on mortality forecasts. The demography and MortalitySmooth packages in R are used to implement life tables and mortality modeling. Smoothing mortality data is necessary to stabilize high variance associated with high age-specific rates, and two smoothing methods are described: weighted constrained penalized regression splines and two-dimensional P-splines. These methods are used to estimate smooth curves for mortality rates, with examples shown for USA male mortality data.

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Prospective life tables depend on forecasting age-specific mortality, with various extrapolative methods available, including the Lee-Carter method, Bayesian...

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  • File Format: PDF
  • File Size: 599 KB
  • Pages: 22
  • Language: EN
  • Total Downloads: 354
  • Last Updated: 3 weeks ago

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