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Andrew Smith Denoising UK house prices 14th April 2010.

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Presentation on theme: "Andrew Smith Denoising UK house prices 14th April 2010."— Presentation transcript:

1 Andrew Smith Denoising UK house prices 14th April 2010

2 2 Regression on a graph Denoising UK house prices Discrete spatial processes Longitudinal data analysis Scatterplot smoothing Image analysis

3 3 Outline UK house price data The need for regression Graph structure Regression on a graph Penalised regression Results and uses of algorithm

4 4 Video available at http://www.maths.bris.ac.uk/~as1637/research/warwick1.wmv

5 5 Regression Seek a (simpler) pattern that explains observed data Model: Data=Signal+Noise Price year,town =True value year,town +σ year Z year,town

6 6 No covariate values Euclidean distance inappropriate Missing values Challenges for existing methods

7 7 Regression on a graph Consider observations Price year,town to be taken at the vertices of a graph Edges of the graph give an idea of closeness 199920002001

8 8 Consider observations Price year,town to be taken at the vertices of a graph Edges of the graph (neighbouring towns) give an idea of closeness Regression on a graph

9 9 Penalised regression on a graph Need to penalise distance from data Penalty term: Sum (over all vertices) of squares of residuals

10 10 Penalised regression on a graph Need to penalise roughness Penalty term: Sum (over all edges) of absolute differences

11 11 Penalised regression on a graph Minimise: Distance from data + λ Roughness Computationally intensive, so use new algorithm

12 12 Video available at http://www.maths.bris.ac.uk/~as1637/research/warwick2.wmv

13 13 Regional analysis The estimate identifies regions of constant value These regions change in a similar way through time

14 14 Regional analysis The estimate identifies regions of constant value These regions change in a similar way through time They are not the same as government office regions

15 15 Summary Detecting a smooth national trend in noisy UK house price data Use regression on a graph Penalise distance from data (vertices) and roughness (edges) arxiv.org/abs/0911.1928 (Kovac & Smith 2009) All house price data courtesy of Halifax


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