BAMP is available as standalone version (version 1.3). The standalone version no longer actively developed.
If you want to use your own ini-files, you have to use a MS-DOS-console:
Please be sure, that the file cygwin1.dll is in the same folder as bamp.exe.
We recommend to convert bamp.ini to unix format using [dos2unix] after editing the file with WordPad. Unpack dos2unix to the bamp folder. After editing and saving bamp.ini, drop the bamp.ini file on the dos2unix icon. After this, BAMP should run smoothly on all Windows versions.
Detailed information on the software, the data and the output can be found in Schmid, Held: Bayesian Age-Period-Cohort Modeling and Prediction - BAMP, Journal of Statistical Software, Vol. 21, Issue 8, Oct 2007.
After you have installed BAMP, edit the bamp.ini file or write your own ini-file. Then start the program by typing
or (if you use bamp.ini) just type
On window-based OS you can also start BAMP with a double click on the BAMP-icon. BAMP then will use the bamp.ini file
BAMP needs input files with the population data and the number of deaths. Both files have to be matrices of number of age groups x number of periods (or transposed, see dataorder). The data has to be separated by blanks.
If you want to get predictions of future death rates, set predictions to 1. Set number of predictions to the number of periods for which you want the predictions. If you also have population projection, set predictions to 3. In order to test the model you can also make prediction for existing data. Then the input files must include this data, the matrices have to be of order number of agegroups x (number of periods + number of predictions). Set deviance to 2 and BAMP will calculate the deviance for the predicted periods.
|cancer data||Path + File of number of deaths|
|population data||Path + File of population number|
|output folder||Path of Folder for output files|
|temp folder||Path of Folder for temporarily files|
|output file||File for general output; 0 = console|
|dataorder||1 if data for one period is in a row, 0 if in a column|
|number of agegroups||Number of agegroups|
|number of periods||Number of periods|
|periods per agegroup||Number of periods in one agegroup|
|predictions||0 = no predictions, 1 = predictions, 2 = predictions for existing data (see deviance)|
|number of predictions||Number of periods to be predicted|
|number of iterations||Number of iterations (including burn in)|
|burn in||Number of iterations for burn in (including tuning)|
|step||Thinning parameter for MCMC simulation|
|tuning||Number of iterations done for tuning|
|samples||1 if you wish to get all samples, 0 else; samples will be written to “temp folder”|
|deviance||0 = don’t compute deviance, 1 = compute deviance, 2 = compute deviance also for predicted periods (only if predictions = 2)|
|age block||0 = don’t compute age effect, 1 = use RW 1, 2 = use RW 2|
|age hyperpar.a / b.||hyperparameters for Priors of precision|
|period block||0 = don’t compute period effect, 1 = use RW 1, 2 = use RW 2|
|period hyperpar.a / b.||hyperparameters for Priors of precision|
|cohort block||0 = don’t compute cohort effect, 1 = use RW 1, 2 = use RW 2|
|cohort hyperpar.a and b.||hyperparameters for Priors of precision|
|z hyperpar.a and b.||hyperparameters for Priors of precision of overdispersion parameter|
|quantile 1 to 5||Quantile of output data; -1 no output|
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