Graham
D.J., McCoy E.J. and Stephens, D.A. (2015) “Approximate Bayesian
inference for double robust estimation.” Bayesian Analysis (acceped).

Tzouras, S., McCoy, E. J., \&
Anagnostopoulos, C. (2015) “Financial time series modeling
using the Hurst exponent,” Physica A:
Statistical Mechanics and its Applications, 425, 50-68.

Graham,
D.J., McCoy, E.J. and Stephens, D.A. (2014) “Quantifying causal effects
of road network capacity expansions on traffic flow and density via a mixed
model propensity score estimator.” Journal of the American Statistical
Association, 109, 509, 1440-1449.

Martin,
J. S., Jasra, A. and McCoy, E. (2014) “Approximate Bayesian Computation
for Smoothing.” Stochastic Analysis and Applications, 32(3), 397-420

Graham,
D. J., McCoy, E. J. and Stephens, D. A. (2013). “Quantifying the effect
of area deprivation on child pedestrian casualties by using longitudinal mixed
models to adjust for confounding, interference and spatial dependence.”
Journal of the Royal Statistical Society: Series A (Statistics in Society),
176, 4, 931-950.

Martin,
J. S., Jasra, A. and McCoy, E. (2013). “Inference for a class of
partially observed point process models.” Annals of the Institute of
Statistical Mathematics, 65(3), 413-437.

Jasra,
A., Singh, S. S., Martin, J. S. and McCoy, E. (2012). “Filtering via
approximate Bayesian computation.” Stat. Comput.,
22, 1223-1237.

Yang,
Z., Walden, A. T. and McCoy, E. J. (2011). “Correntropy:
Implications of nonGaussianity for the moment
expansion and deconvolution.” Signal
Processing, 91(4), 864-876.

Au-Yeung,
S. W. M., Harder, U., McCoy, E. J. and Knottenbelt, W. J. (2009).
“Predicting patient arrivals to an accident and
emergency department.” Emergency Medicine Journal, 26(4), 241-244.

Hancock,
J., Watson-Lamprey, J., Abrahamson, N. A., Bommer, J. J., Markatis, A., McCoy,
E. J., and Mendis, R. (2006). “An improved method of matching response
spectra of recorded earthquake ground motion using wavelets." Journal of
Earthquake Engineering, 10(spec01), 67-89.

Olhede,
S C., McCoy E. J., and Stephens D. A. "Large sample properties of the periodogram estimator of seasonally persistent
processes." Biometrika 91.3 (2004): 613-628

McCoy,
E. J., and Stephens, D. A. (2004) "Bayesian time series analysis of
periodic behaviour and spectral structure." International Journal of
Forecasting 20.4: 713-730.

McCoy,
E. J. (1999) "Wavelet regression: a penalty function approach."
Proceeding of the 52nd session of the International Statistical Institute.

McCoy,
E. J., Walden, A. T., and Percival, D. B.. "Multitaper spectral estimation of power law
processes." Signal Processing, IEEE Transactions on 46.3 (1998): 655-668.

Walden,
A. T., Percival, D. B., and McCoy, E. J..
"Spectrum estimation by wavelet thresholding of multitaper estimators." Signal Processing, IEEE
Transactions on 46.12 (1998): 3153-3165.

McCoy,
E. J., and Walden, A. T. "Wavelet analysis and synthesis of stationary
long-memory processes." Journal of Computational and Graphical Statistics
5.1 (1996): 26-56.

Walden,
A. T., McCoy, E. J., and Percival, D. B. "The effective bandwidth of a multitaper spectral estimator." Biometrika
82.1 (1995): 201-214.

Walden,
A. T., McCoy, E.J.,
and Percival, D B. "The variance of multitaper
spectrum estimates for real Gaussian processes." Signal Processing, IEEE
Transactions on 42.2 (1994): 479-482.

I had a few font
hassles when I tried to re LaTeX this,

I guess the system LaTeX has been updated since late 1994!)

My
PhD centred around the analysis and synthesis of
long-memory processes, particularly from a spectral analysis viewpoint. Both the
use of the discrete wavelet transform and multitaper spectral estimation proved
excellent tools in analyzing such processes, and I further investigated the
properties of these methods.

Here it is, missing
some boldmaths (unix compressed, beware it's fairly
big: about 1.7 MBytes) report.ps.Z

I also have it gzipped
(about 1MByte) report.ps.gz

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