On 28th November OxTalks will move to the new Halo platform and will become 'Oxford Events' (full details are available on the Staff Gateway).
There will be an OxTalks freeze beginning on Friday 14th November. This means you will need to publish any of your known events to OxTalks by then as there will be no facility to publish or edit events in that fortnight. During the freeze, all events will be migrated to the new Oxford Events site. It will still be possible to view events on OxTalks during this time.
If you have any questions, please contact halo@digital.ox.ac.uk
A new goodness-of-fit test for continuous conditional distributions, based on the Pearson type test of independence, is proposed. The test exploits the fact that, under a correct specification, the conditional probability integral transform of the explained variable is independent of the explanatory variables. Unlike existing Pearson’s tests for conditional distributions, the test statistic proposed is distributed as a chi-square with known degrees of freedom when using general partitions that may depend on the sample. We propose alternative data grouping algorithms in multiple dimensions to construct partitions for constructing tests with different properties. The finite sample performance of the test is investigated by means of Monte Carlo simulations.
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