  The method of closure testing for analysing the effectiveness of a PDF
fitting procedure is discussed. In order to pass a closure test, a fitting
methodology must be able to reproduce a known generating function in a fit to
an ideal pseudo-dataset generated by that PDF up to the level of experimental
uncertainty in the data. Here we present an initial study of the closure
property of the NNPDF fitting methodology. An idealised pseudo-dataset is
generated by a set of toy PDFs that differ substantially from previous NNPDF
determinations. In a fit to this pseudodata, the NNPDF methodology is shown to
be able to reproduce well the toy PDFs used as a generating function.
