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A mortality model based on a mixture distribution function.

Stefano Mazzuco1, Bruno Scarpa1, Lucia Zanotto1

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Summary
This summary is machine-generated.

A novel mortality model, blending half-normal and skew-normal distributions, accurately captures diverse mortality patterns. This six-parameter model offers a balanced alternative to existing complex or limited mortality prediction tools.

Keywords:
accident humphalf-normal distributionmixture distributionmortality modelskew-bimodal-normal distribution

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Area of Science:

  • Demography
  • Biostatistics
  • Actuarial Science

Background:

  • Accurate mortality modeling is crucial for actuarial science and public health.
  • Existing models like Siler and Heligman-Pollard have limitations in flexibility or parameterization.
  • A need exists for a parsimonious yet adaptable mortality model.

Purpose of the Study:

  • To propose a new flexible mortality model using a mixture distribution.
  • To evaluate the performance of the proposed model against established mortality models.
  • To offer a compromise between model complexity and data-fitting capabilities.

Main Methods:

  • A novel six-parameter mortality model was developed by mixing a half-normal distribution with a generalized skew-normal distribution.
  • The proposed mixture model was fitted to various mortality data schedules.
  • Performance was assessed by comparing the model's fit with the Siler and Heligman-Pollard models.

Main Results:

  • The proposed six-parameter mixture model demonstrated a good fit across diverse mortality patterns.
  • The model effectively captured phenomena like 'accident humps' that the Siler model misses.
  • It provides a more parsimonious alternative to the Heligman-Pollard model while maintaining good fit.

Conclusions:

  • The proposed mixture distribution mortality model is a flexible and effective tool for demographic and actuarial analysis.
  • This model offers a practical balance, overcoming limitations of both the Siler and Heligman-Pollard models.
  • It represents a valuable advancement in mortality modeling research.