Flow of Commands in Dismod-ATΒΆ
There are a few different ways to use Dismod-AT to examine data. They correspond to different sequences of Dismod-AT commands.
Stream Out Prevalence The simplest use of Dismod-AT is to ask it to run the ordinary differential equation on known rates and produce prevalence, death, and integrands derived from these.
Precondition Provide known values for all rates over the whole domain. List the integrands desired for the output.
Run predict on those rates.
Postcondition Dismod-AT places any requested integrands in its predict table. These can be rates, prevalence, death, or any of the integrands.
Simple Fit to a Dataset This describes a fit with the simplest way to determine uncertainty.
Precondition The input data is observations, with standard deviations, of any of the known integrands.
Run fit on those observations to produce rates and covariate multipliers.
Run predict on the rates to produce integrands.
Postcondition Integrands are in the predict table.
Fit with Asymptotic Uncertainty This fit produces some values of uncertainty.
Precondition The input data is observations, with standard deviations, of any of the known integrands.
Run fit on those observations to produce rates and covariate multipliers.
Run sample asymptotic.
Postcondition Integrands are in the predict table.
Fit with Simulated Uncertainty This uses multiple predictions in order to obtain a better estimate of uncertainty.
Precondition The input data is observations, with standard deviations, of any of the known integrands.
Run fit on those observations to produce rates and covariate multipliers.
Run simulate to generate simulations of measurements data and priors.
Run sample simulate.
Postcondition Integrands are in the predict table.