WIP: Non-parametric statistics

This is a work-in-progress, developed with @nicholst, to model non-parametric inference.

The proposed modifications are as follows:
- New attribute `nidm:isParametric` in `nidm:Inference` to specify whether parametric or non-parametric inference is performed.
- New optional entity `nidm:NonParametricNullDistribution` (used by `nidm:Inference` and only available if `isParametric` = `true`) with attributes: `nidm:numberOfPermutations`, `nidm:varianceSmoothingFWHM`, `nidm:exchangeabilityBlockSize` (optional).
- New optional attribute `nidm:varianceSmoothingFWHM` in `nidm:StatisticMap` to specify the degree of variance smoothing for `Pseudo-TStatistic`.

![image](https://cloud.githubusercontent.com/assets/5374264/5340271/a32eda2a-7ee2-11e4-97a4-f7d82adf9207.png)