karup_king

Separate grouped-age data to simple ages data using Karup-King separation factors.

The use of overparameterization is proposed with combinatorial analysis to test a broader spectrum of possible ARIMA models.
In the selection of ARIMA models, the most traditional methods such as correlograms or others, do not usually cover many alternatives to define the number of coefficients to be estimated in the model, which represents an estimation method that is not the best.
The popstudy package contains several tools for statistical analysis in demography and time series based in Shryock research (Shryock et. al. (1980) <https://books.google.co.cr/books?id=8Oo6AQAAMAAJ>).

Cesar Gamboa

popstudy

Applied Techniques to Demographic and Time Series Analysis

Cesar Gamboa-Sanabria

karup_king function

<dl><dt>data</dt>
<dd>data.frame. A dataset with two variables: <code>age</code>, the group age each 5 years; and <code>pop</code>, the population for that age.</dd></dl>

Arguments

Author

karup_king — karup_king

<dl>

<dt>data</dt>
<dd>data.frame. A dataset with two variables: <code>age</code>, the group age each 5 years; and <code>pop</code>, the population for that age.</dd>

</dl>

karup_king: karup_king

Description

Usage

Value

Arguments

Author

References

See Also

Examples