Using skew-logistic probability density function as a model for age-specific fertility rate pattern.

Area of Science:

• Demography
• Biostatistics

Background:

• Fertility rate is a key global demographic indicator.
• Existing models for age-specific fertility rates include mixture probability density functions and skew-normal models.
• Skew-normal models offer flexibility for unimodal and bimodal fertility patterns but can be improved.

Purpose of the Study:

• To introduce the skew-logistic probability density function as a superior model for age-specific fertility rates.
• To demonstrate the improved performance of the skew-logistic model over the skew-normal model.

Main Methods:

• The study proposes and evaluates the skew-logistic probability density function.
• Model performance is assessed by comparing residuals and parameter estimation precision against the skew-normal model.

Main Results:

• The skew-logistic probability density function demonstrated lower residuals than the skew-normal model.
• The new model provides more precise parameter estimation for fertility rate data.

Conclusions:

• The skew-logistic probability density function is a more effective and precise tool for modeling age-specific fertility rates.
• This advancement offers enhanced accuracy in demographic analysis and fertility studies.