Case Study for Life Tables Analysis

This example shows how to use the basic workflow for life tables.

Load the life table data file.

`load us_lifetable_2009`

Calibrate life table from survival data with the default `heligman-pollard` parametric model.

`a = lifetablefit(x, lx);`

Generate life table series from the calibrated mortality model.

```qx = lifetablegen((0:100), a); display(qx(1:40,:))```
``` 0.0063 0.0069 0.0057 0.0005 0.0006 0.0004 0.0002 0.0003 0.0002 0.0002 0.0002 0.0002 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0002 0.0002 0.0001 0.0002 0.0002 0.0002 0.0002 0.0003 0.0002 0.0003 0.0004 0.0002 0.0004 0.0005 0.0002 0.0005 0.0006 0.0003 0.0006 0.0008 0.0003 0.0007 0.0009 0.0003 0.0008 0.0011 0.0003 0.0008 0.0012 0.0004 0.0009 0.0013 0.0004 0.0009 0.0014 0.0005 0.0010 0.0014 0.0005 0.0010 0.0015 0.0005 0.0010 0.0015 0.0006 0.0010 0.0015 0.0006 0.0010 0.0015 0.0007 0.0010 0.0014 0.0007 0.0011 0.0014 0.0007 0.0011 0.0014 0.0008 0.0011 0.0014 0.0008 0.0011 0.0014 0.0009 0.0011 0.0014 0.0009 0.0012 0.0015 0.0010 0.0012 0.0015 0.0011 0.0013 0.0016 0.0011 0.0014 0.0017 0.0012 0.0015 0.0018 0.0013 ```

Plot the `qx` series and display the legend. The series `qx` is the conditional probability that a person at age $x$ will die between age $x$ and the next age in the series

```plot((0:100), log(qx)); legend(series, 'location', 'southeast'); title('Conditional Probability of Dying within One Year of Current Age'); xlabel('Age'); ylabel('Log Probability');```