Provides functions for using a model life table system generated from the Human Mortality Database
|License:||GPL (>= 2)|
mortmod is the mortality model that is the basis for the system. The user can supply the two input parameters - family and level - and a complete mortality rate schedule can be generated. If the user has some measure of child mortality (or a partial schedule) and optionally 45q15, the function
hmd.DA can be used to find the appropriate family. Then
alpha.e0 can calculate an alpha value to generate a life table with a desired life expectancy. The function
mod.lt combines the steps outlined above. It will find the family and level based on the child (and possibly adult) mortality indicator and a desired life expectancy and return a complete life table generated with the appropriate input parameter values.
There is a graphical user interface implemented in the package that allows for generating model life tables, exporting them and plotting various measures of the life table. It can be invoked using the function
Note: In version 1.0, the calibration data set has been updated. Most recent HMD calibration data downloaded February 2015.
David J. Sharrow, GUI by Hana Sevcikova
Maintainer: David Sharrow <firstname.lastname@example.org>
S. Clark and D. Sharrow (2011) "Contemporary Model Life Tables for Developed Countries: An Application of Model-Based Clustering." Paper presented at the annual meeting of the Population Association of America. http://paa2011.princeton.edu/abstracts/111808
C. Fraley and A. E. Raftery (2002) "Model-based clustering, discriminant analysis, and density estimation." Journal of the American Statistical Association 97:611-631.
C. Fraley, A. E. Raftery, T. B. Murphy, L. Scrucca (2012) "mclust Version 4 for R: Normal Mixture Modeling for Model-Based Clustering, Classification, and Density Estimation", Technical Report no. 597, Department of Statistics, University of Washington
Human Mortality Database University of California, Berkeley (USA), and Max Planck Institute for Demographic Research (Germany). Available at www.mortality.org or www.humanmortality.de (data downloaded February 2015).
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# first get the appropriate family # hmd.DA(x=.09, sex="male", child.mort=4, adult.mort=.28)$classification # then get the appropriate level (alpha) # alpha.e0(pattern=1, e0.target=59, sex="male") # put in the family and alpha to model to produce complete schedule # mortmod(pattern=1, alpha=.034, sex="male")
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