Estimates the parameters of the statistical model for the integrated version the CASTLE algorithm based on a set of training samples, assumed to have no mutant DNA present.

`train_integrated_ddpcr_model(background_samples, abc_grid_resolution = 25)`

- background_samples
`data.frame`

with cancer negative training samples as rows. These are the samples used to train/estimate the parameters of the model. At least the following columns should be present:`WildtypeOnlyDroplets`

`MutantOnlyDroplets`

`DoubleNegativeDroplets`

`DoublePositiveDroplets`

If data from QuataSoft is available, these can be imported using

`import_QS_files`

.- abc_grid_resolution
The resolution of the 3D-grid on which the integrated LR-test statistic is approximated. Default is 25 (equal to a grid of 25^3 = 15,625 points).

List of parameter estimates for the integrated CASLTE model. This
should be used as input for `test_tumor_sample_integrated`

.

In the test an integrated version of the Likelihood Ratio test
statistic is used, and this is approximated using a Riemann sum on a
3D-grid. The parameter `abc_grid_resolution`

controls this
approximation as the sum is calculated on `abc_grid_resolution^3`

points. Higher values give better approximation but longer computation
times.