Pca

* Added parameter in `biplot `and `biplot3d `to choose the PC axes.


fig, ax = model.biplot(PC=[0, 1])
fig, ax = model.biplot3d(PC=[0, 1, 2])

* added doi

* Fix in case PCs are selected based on percentage explained variance. In cases when new samples needed to be transformed with the existing model, an error occurred.
* Licence added to the setup file

* Fix for plot in case only 1PC is detected.

* Added functionality to train/infer mode for outlier detection in Hotelling's T2 and SPE 15 and 16
* Added functionality to use lists as input for the model 17

* Detection of outliers is now optional. If you do not want to detect outliers use the following during initialiation: detect_outliers=None. The detection of outliers can now be set by: detect_outliers=['ht2', 'spe'] (default)