Online Lee Carter Mortality forecasting
Python Matlab R Shell M CSS
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webbs Fixed offset issues in coherent
* Start the AR1 simulation of resid at the correct place

* Use offset (not resid!) to get the kt simulation started

* FINALLY graph correctly -- wasted LOTS of hours because was debugging
* to a bad graph

* Tried to refactor a little and fix some wonky comments etc.
Latest commit 094c1d4 May 6, 2011
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DATABASE
DESIGN
INSTALLATION
INTERNET_APPLICATION
LCFIT_TUT
MAINTENANCE
OLDER_CODE
TESTING
UTILS
README

README

LCFIT -- Lee Carter FITter

LCFIT is a python program that implements the Lee-Carter mortality
model and forecasting algorithm.  Basically, the Lee-Carter model uses
the Singular Value Decomposition to decompose a matrix of mortality
rates into a single time series ("k_t") showing the overall mortality
trend, a base set of age specific mortality rates ("a_x"), and a
vector ("b_x") that describes the amount of mortality change at a give
age for a unit of overall mortality change.

This project uses mod_python + apache to serve the pages, postgresql
to store the data, scipy + numpy to do the calculations, and
matplotlib to make graphics.

This code repository also contains some code written in R and Matlab
to perform LCFIT in other contexts.

Many of the papers that were used to develop this code can be found on
Professor Ronald D. Lee's CEDA website:

http://www.ceda.berkeley.edu/peoplenew/rlee.html

This work was funded by CEDA as well.

An example of this code in action can be found at

http://lcfit.demog.berkeley.edu