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Modifying the t test for assessing the correlation between two spatial processes
- P. Dutilleul, P. Clifford, S. Richardson, D. Hémon
- Mathematics
- 1 March 1993
Clifford, Richardson, and Hm they require the estimation of an effective sample size that takes into account the spatial structure of both processes. Clifford et al. developed their method on the…
Improved particle filter for nonlinear problems
- J. Carpenter, P. Clifford, P. Fearnhead
- Engineering
- 1 February 1999
The Kalman filter provides an effective solution to the linear Gaussian filtering problem. However where there is nonlinearity, either in the model specification or the observation process, other…
Assessing the significance of the correlation between two spatial processes.
- P. Clifford, S. Richardson, D. Hémon
- PsychologyBiometrics
- 1 March 1989
TLDR
A model for spatial conflict
- P. Clifford, A. Sudbury
- Environmental Science
- 1 December 1973
Two species compete for territory along their mutual boundary. The species are fairly matched and the result of conflict is the invasion by one of the species of territory held by the other. A simple…
Sequential Monte Carlo p-values
- J. Besag, P. Clifford
- Mathematics
- 1 June 1991
SUMMARY The assessment of statistical significance by Monte Carlo simulation may be costly in computer time. This paper looks at a number of ways of calculating exact Monte Carlo p-values by…
An improved particle filter for non-linear problems
- J. Carpenter, P. Clifford, P. Fearnhead
- Engineering
- 1 February 1999
The Kalman filter provides an effective solution to the linear Gaussian filtering problem. However where there is nonlinearity, either in the model specification or the observation process, other…
On‐line inference for hidden Markov models via particle filters
- P. Fearnhead, P. Clifford
- Computer Science
- 1 November 2003
Summary. We consider the on‐line Bayesian analysis of data by using a hidden Markov model, where inference is tractable conditional on the history of the state of the hidden component. A new…
Generalized Monte Carlo significance tests
- J. Besag, P. Clifford
- Mathematics
- 1 December 1989
SUMMARY Simple Monte Carlo significance testing has many applications, particularly in the preliminary analysis of spatial data. The method requires the value of the test statistic to be ranked among…
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