Statistics Papers by Matt Wand


Under consideration for publication or in press


McLean, M.W. and Wand, M.P.
Variational Message Passing for Elaborate Response Regression Models.
[PDF file]

Published in 2017


Wand, M.P.
Fast Approximate Inference for Arbitrarily Large Semiparametric Regression Models
via Message Passing (with discussion).
Journal of the American Statistical Association, (2017), 112, 137-168.
[PDF file of article and discussion] [PDF file of article's web-supplement]

Kim, A.S.I. and Wand, M.P.
On Expectation Propagation for Generalised, Linear and Mixed Models.
Australian and New Zealand Journal of Statistics, (2017), 59, xxx-xxx (page numbers pending).
[PDF file]

Nolan, T.H. and Wand, M.P.
Accurate Logistic Variational Message Passing: Algebraic and Numerical Details.
Stat, (2017), 6, 102-112.
[PDF file of main article] [PDF file of web-supplement]

Luts, J., Wang, S.S.J., Ormerod, J.T. and Wand, M.P.
Semiparametric Regression Analysis via Infer.NET.
Journal of Statisical Software, (2017), xxx, xxx-xxx (volume and page numbers pending).
[PDF file]

Published in 2016


Ryan, L.M., Wand, M.P. and Malecki, A.A.
Bringing Coals to Newcastle.
Significance, (2016), 13, 32-37.
[PDF file]

Rohde, D. and Wand, M.P.
Semiparametric Mean Field Variational Bayes: General Principles and Numerical Issues.
Journal of Machine Learning Research, (2016), 17 (172), 1-47.
[PDF file]

Delaigle, A. and Wand, M.P.
A Conversation with Peter Hall.
Statistical Science, (2016), 31, 275-304.
[PDF file]

Dubossarsky, E., Friedman, J.H., Ormerod, J.T. and Wand, M.P.
Wavelet-based Gradient Boosting.
Statistics and Computing, (2016), 26, 93-105.
[PDF file]

Lee, C.Y.Y. and Wand, M.P.
Variational Methods for Fitting Complex Bayesian Mixed Effects Models to Health Data.
Statistics in Medicine, (2016), 35, 165-188.
[PDF file]

Kim, A.S.I. and Wand, M.P.
The Explicit Form of Expectation Propagation for a Simple Statistical Model.
Electronic Journal of Statistics, (2016), 10, 550-581.
[PDF file] [ZIP archive file (computer code)]

Lee, C.Y.Y. and Wand, M.P.
Streamlined Mean Field Variational Bayes for Longitudinal and Multilevel Data Analysis.
Biometrical Journal, (2016), 58, 868-895.
[PDF file]

Published in 2015


Menictas, M. and Wand, M.P.
Variational Inference for Heteroscedastic Semiparametric Regression.
Australian and New Zealand Journal of Statistics, (2015), 57, 119-138.
[PDF file]

Luts, J. and Wand, M.P.
Variational Inference for Count Response Semiparametric Regression.
Bayesian Analysis, (2015), 10, 991-1023.
[PDF file]

Published in 2014


Luts, J., Broderick, T. and Wand, M.P.
Real-time Semiparametric Regression.
Journal of Computational and Graphical Statistics, (2014), 23, 589-615.
[PDF file]

Neville, S.E., Ormerod, J.T. and Wand, M.P.
Mean Field Variational Bayes for Continuous Sparse Signal Shrinkage: Pitfalls and Remedies.
Electronic Journal of Statistics, (2014), 8, 1113-1151.
[PDF file]

Wand, M.P.
Fully Simplified Multivariate Normal Updates in Non-Conjugate Variational Message Passing.
Journal of Machine Learning Research, (2014), 15, 1351-1369.
[PDF file]

Published in 2013


Pham, T., Ormerod, J.T. and Wand, M.P.
Mean Field Variational Bayesian Inference for Nonparametric Regression with Measurement Error.
Computational Statistics and Data Analysis, (2013), 68, 375-387.
[PDF file]

Huang, A. and Wand, M.P.
Simple Marginally Noninformative Prior Distributions for Covariance Matrices.
Bayesian Analysis, (2013), 2, Number 2, 439-452.
[PDF file]

Menictas, M. and Wand, M.P.
Variational Inference for Marginal Longitudinal Semiparametric Regression.
Stat, (2013), 2, 61-71.
[PDF file]

Published in 2012


Wand, M.P. and Ormerod, J.T.
Continued Fraction Enhancement of Bayesian Computing.
Stat, (2012), 1, 31-41.
[PDF file]

Ormerod, J.T. and Wand, M.P.
Gaussian Variational Approximate Inference for Generalized Linear Mixed Models.
Journal of Computational and Graphical Statistics, (2012), 21, 2-17.
[PDF file of main article] [PDF file of web-supplement]

Published in 2011


Hall, P., Pham, T., Wand, M.P. and Wang, S.S.J.
Asymptotic Normality and Valid Inference for Gaussian Variational Approximation.
The Annals of Statistics, (2011), 39, 2502-2532.
[PDF file]

Faes, C., Ormerod, J.T. and Wand, M.P.
Variational Bayesian Inference for Parametric and Nonparametric Regression with Missing Data.
Journal of the American Statistical Association, (2011), 106, 959-971.
[PDF file of main article] [PDF file of web-supplement]

Neville, S.E., Palmer, M.J. and Wand, M.P.
Generalized Extreme Value Additive Model Analysis via Mean Field Variational Bayes.
Australian and New Zealand Journal of Statistics, (2011), 53, 305-330.
[PDF file]

Hall, P., Ormerod, J.T. and Wand, M.P.
Theory of Gaussian Variational Approximation for a Generalised Linear Mixed Model.
Statistica Sinica, (2011), 21, 269-389.
[PDF file]

Chacon, J.E., Duong, T. and Wand, M.P.
Asymptotics for General Multivariate Kernel Density Derivative Estimators.
Statistica Sinica, (2011), 21, 807-840.
[PDF file]

Wand, M.P., Ormerod, J.T., Padoan, S.A. and Fruhwirth, R.
Mean Field Variational Bayes for Elaborate Distributions.
Bayesian Analysis, (2011), 6, 847-900.
[PDF file]

Wang, S.S.J and Wand, M.P.
Using Infer.NET for Statistical Analyses.
The American Statistician, (2011), 65, 115-126.
[PDF file]

Wand, M.P. and Ormerod, J.T.
Penalized Wavelets: Embedding Wavelets into Semiparametric Regression.
Electronic Journal of Statistics, (2011), 5, 1654--1717.
[PDF file (article)] [ZIP archive file (computer code)]

Goldsmith, J., Wand, M.P. and Crainiceanu, C.
Functional Regression via Variational Bayes.
Electronic Journal of Statistics, (2011), 5, 572--602.
[PDF file]

Published in 2010


Marley, J.K. and Wand, M.P.
Non-Standard Semiparametric Regression via BRugs.
Journal of Statistical Software, (2010), Volume 37, Issue 5, 1-30.
[ PDF file; Code and Data Files]

Al Kadiri, M., Carroll, R.J. and Wand, M.P.
Marginal Longitudinal Semiparametric Regression via Penalized Splines.
Statistics and Probability Letters, (2010), 80, 1242-1252.
[PDF file]

Ormerod, J.T. and Wand, M.P.
Explaining Variational Approximations.
The American Statistician, (2010), 64, 140-153.
[PDF file]

Samworth, R.J. and Wand, M.P.
Asymptotics and Optimal Bandwidth Selection for Highest Density Region Estimation.
The Annals of Statistics, (2010), 38, 1767-1792.
[PDF file]

Naumann, U., Luta, G. and Wand, M.P.
The curvHDR Method for Gating Flow Cytometry Samples.
BMC Bioinformatics, (2010), 11:44, 1-13.
[PDF file]

Kauermann, G., Ormerod, J.T. and Wand, M.P.
Parsimonious Classification via Generalised Linear Mixed Models.
Journal of Classification, (2010), 27, 89-110.
[PDF file]

Published in 2009


Ruppert, D., Wand, M.P. and Carroll, R.J.
Semiparametric Regression During 2003-2007.
Electronic Journal of Statistics, (2009), 3, 1193-1256.
[PDF file]

Staudenmayer, J., Lake, E.E. and Wand, M.P.
Robustness for General Design Mixed Models Using the t-Distribution.
Statistical Modelling, (2009), 9, 235-255.
[PDF file]

Naumann, U. and Wand, M.P.
Automation in High-Content Flow Cytometry Screening.
Cytometry Part A, (2009), 75A, 789-797.
[PDF file]

Pearce, N.D. and Wand, M.P.
Explicit Connections between Longitudinal Data Analysis and Kernel Machines.
Electronic Journal of Statistics, (2009), 3, 797-823.
[PDF file]

Duong, T., Koch, I. and Wand, M.P.
Highest Density Difference Region Estimation with Application to Flow Cytometric Data.
Biometrical Journal, (2009), 51, 504-521.
[PDF file]

Wand, M.P.
Semiparametric Regression and Graphical Models.
[PDF file]
This article was published in Australian and New Zealand
Journal of Statistics, 2009; 51: 9 to 41, available online
at Blackwell Synergy (www.blackwell-synergy.com).

Ormerod, J.T. and Wand, M.P.
Comment on Paper by Rue, Martino and Chopin.
Journal of the Royal Statistical Society, Series B, 71, 377-378.
[PDF file]

Published in 2008


Fan, Y., Leslie, D.S. and Wand, M.P.
Generalised Linear Mixed Model Analysis via Sequential Monte Carlo Sampling.
Electronic Journal of Statistics, (2008), 2, 916-938.
[ PDF file]

Duong, T., Cowling, A., Koch, I. and Wand, M.P.
Feature Significance for Multivariate Kernel Density Estimation.
Computational Statistics and Data Analysis, (2008), 52, 4225-4242
[PDF file]

Kuo, F., Dunsmuir, W.T.M., Sloan, I.H., Wand, M.P. and Womersley, R.S.
Quasi-Monte Carlo for Highly Structured Generalised Response Models.
Methodology and Computing in Applied Probability, (2008), 10, 239-275.
[PDF file]

Smith, A.D.A.C. and Wand, M.P.
Streamlined Variance Calculations for Semiparametric Mixed Models.
Statistics in Medicine, (2008), 27, 435-448.
[ PDF file] [Appendix code]

Wand, M.P. and Ormerod, J.T.
On Semiparametric Regression with O'Sullivan Penalised Splines.
This article was published in Australian and New Zealand
Journal of Statistics, 2008; 50: 179 to 198, available online
at Blackwell Synergy (www.blackwell-synergy.com).
[PDF file] [Correction notice (PDF file)] [Appendix code]

Ormerod, J.T., Wand, M.P. and Koch, I.
Penalised Spline Support Vector Classifiers: Computational Issues.
Computational Statistics, (2008), 23, 623-641.
[PDF file]

Padoan, S.A. and Wand, M.P.
Mixed Model-based Additive Models for Sample Extremes.
Statistics and Probability Letters, (2008), 78, 2850-2858.
[PDF file]

Published in 2007


Wand, M.P.
Fisher Information for Generalised Linear Mixed Models.
Journal of Multivariate Analysis, (2007), 98, 1412-1416.
[PDF file]

Ganguli, B. and Wand, M.P.
Feature significance in generalized additive models.
Statistics and Computing, (2007). 17, 179-192.
[ PDF file]

Published in 2006


Wand, M.P.
Support Vector Machine Classification.
Parabola, (2006), 42 (2), 21-37.
[PDF file] [ co lo ur version PDF file]

Pearce, N.D. and Wand, M.P.
Penalised Splines and Reproducing Kernel Methods.
The American Statistician, (2006), 60, 233-240.
[ PDF file]

Zhao, Y., Staudenmayer, J., Coull, B.A. and Wand, M.P.
General Design Bayesian Generalized Linear Mixed Models.
Statistical Science, (2006), 21, 35-51.
[PDF file]

Ganguli, B. and Wand, M.P.
Additive Models for Geo-Referenced Failure Time Data.
Statistics in Medicine, 2004, 25, 2469-2482.
[PDF file]

Published in 2005


Crainiceanu, C., Ruppert, D. and Wand, M.P.
Bayesian Analysis for Penalized Spline Regression Using WinBUGS.
Volume 14, 2005, Issue 14 of Journal of Statistical Software, 1-24.
[PDF file]

Ganguli, B., Staudenmayer, J. and Wand, M.P.
Additive Models with Predictors Subject to Measurement Error.
[PDF file]
This article was published in Australian and New Zealand
Journal of Statistics, 2005; 47: 193 to 202, available online
at Blackwell Synergy (www.blackwell-synergy.com).

Durban, M., Harezlak, J., Wand, M.P. and Carroll, R.J.
Simple Fitting of Subject-specific Curves for Longitudinal Data.
Statistics in Medicine, (2005), 24, 1153-1167.
[PDF file]

Crainiceanu, C., Ruppert, D., Claeskens, G. and Wand, M.P.
Exact Likelihood Ratio Tests for Penalised Splines.
Biometrika, (2005), 92, 91-103.
[PDF file]

Salganik, M.P., Milford, E.L., Hardie, D.L., Shaw, S. and Wand, M.P.
Classifying Antibodies using Flow Cytometry Data: Class Prediction and Class Discovery.
Biometrical Journal, (2005), 47, 740-745.
[PDF file]

Ganguli, B. and Wand, M.P.
SemiPar 1.0 Users' Manual.
[PDF file]

Published in 2004


Salganik, M.P., Wand, M.P. and Lange, N.
Comparison of Feature Significance Quantile Approximations.
[PDF file]
This article was published in Australian and New Zealand
Journal of Statistics, 2004; 46: 569 to 581, available online
at Blackwell Synergy (www.blackwell-synergy.com).

Ganguli, B. and Wand, M.P.
Feature Significance in Geostatistics.
Journal of Computational and Graphical Statistics, 2004.
13, 954-973
[PDF file]

Ngo, L. and Wand, M.P.
Smoothing with Mixed Model Software.
Volume 9, 2004, Issue 1 of Journal of Statistical Software, 1-54.
[paper, code and data]

Published in 2003


Kammann, E.E. and Wand, M.P.
Geoadditive Models.
Journal of the Royal Statistical Society, Series C, 52, 1-18.
[PDF file]

Wand, M.P.
Smoothing and Mixed Models.
Computational Statistics, 18, 223-249.
[PDF file]

Published in 2002


Wand, M.P.
Vector Differential Calculus in Statistics.
The American Statistician, 56, 55-62.
[PDF file]

Aerts, M., Claeskens, G. and Wand, M.P.
Some Theory for Penalized Spline Generalized Additive Models.
Journal of Statistical Planning and Inference, 103, 455-470.
[PDF file]

Cai, T., Hyndman, R.J. and Wand, M.P.
Mixed Model-Based Hazard Estimation.
Journal of Computational and Graphical Statistics, 11, 784-798.
[PDF file]

Betensky, R.A., Lindsey, J.C., Ryan, L.M. and Wand, M.P.
A Local Likelihood Proportional Hazards Model for Interval Censored Data.
Statistics in Medicine, 21, 263-275.
[PDF file]

Published in 2001


Mammen, E., Marron, J.S., Turlach, B.A. and Wand, M.P.
A General Projection Framework for Constained Smoothing.
Statistical Science, 16, 232-248.
[PDF file]

Coull, B.A., Schwartz, J. and Wand, M.P.
Respiratory Health and Air Pollution: Additive Mixed Model Analyses.
Biostatistics, 2, 337-349.
[PDF file]

Coull, B.A., Ruppert, D. and Wand, M.P.
Simple Incorporation of Interactions into Additive Models.
Biometrics, 57, 539-545.
[PDF file]

Parise, H., Wand, M.P., Ruppert, D. and Ryan L.
Incorporation of Historical Controls Using Semiparametric Mixed Models.
Journal of the Royal Statistical Society, Series C, 50, 31-42.
[PDF file]

French, J.L., Kammann, E.E. and Wand, M.P.
Comment on Paper by Ke and Wang.
Journal of the American Statistical Association, 96, 1285-1288.
[PDF file]

Published in 2000


Wand, M.P.
A Comparison of Regression Spline Smoothing Procedures.
Computational Statistics, 15, 443-462.
[PDF file]

Thurston, S.W., Wand, M.P. and Wiencke, J.K.
Negative Binomial Additive Models.
Biometrics, 56, 139-144.
[PDF file]

Zanobetti, A., Wand, M.P., Schwartz, J. and Ryan, L.M.
Generalized Additive Distributed Lag Models: Quantifying Mortality Displacement.
Biostatistics, 1, 279-292.
[PDF file]

Published in 1999


Wand, M.P.
A Central Limit Theorem for Local Polynomial Backfitting Estimators.
Journal of Multivariate Analysis, 70, 57-65.
[PDF file]

Wand, M.P.
On the Optimal Amount of Smoothing in Penalized Spline Regression.
Biometrika, 86, 936-940.
[PDF file]

Opsomer, J.D., Ruppert, D., Wand, M.P., Holst, U. and Hössjer, O.
Kriging with Nonparametric Variance Function Estimation.
Biometrics, 55, 704-710.
[PDF file]

Gijbels, I., Pope, A. and Wand, M.P.
Understanding Exponential Smoothing via Kernel Regression.
Journal of the Royal Statistical Society, Series B, 61, 39-50.
[PDF file]

Betensky, R.A., Lindsey, J.C., Ryan, L.M. and Wand, M.P.
Local EM Estimation of the Hazard Function for Interval Censored Data.
Biometrics, 55, 238-245.
[PDF file]

Brumback, A., Ruppert, D. and Wand, M.P.
Comment on Paper by Shively, Kohn and Wood.
Journal of the American Statistical Association, 94, 794-797.
[PDF file]

Published in 1998


Wand, M.P.
Finite Sample Performance of Deconvolving Density Estimators.
Statistics and Probability Letters, 37, 131-139.
[PDF file]

Augustyns, I. and Wand, M.P.
Bandwidth Selection for Local Polynomial Smoothing of Multinomial Data.
Computational Statistics, 13, 447-461.
[PDF file]

Published in 1997


Wand, M.P.
Data-based Choice of Histogram Bin Width.
The American Statistician, 51, 59-64.
[PDF file]

Hyndman, R.J. and Wand, M.P.
Nonparametric Autocovariance Function Estimation.
Australian Journal of Statistics, 39, 337-354.
[PDF file]

Ruppert, D., Wand, M.P., Holst, U. and Hössjer, O.
Local Polynomial Variance Function Estimation.
Technometrics, 39, 262-273.
[PDF file]

Carroll, R.J., Fan, J. and Wand, M.P.
Generalized Partially Linear Single-Index Models.
Journal of the American Statistical Association, 92, 477-489.
[PDF file]

Wand, M.P. and Gutierrez, R.G.
Exact Risk Approaches to Smoothing Parameter Selection.
Journal of Nonparametric Statistics, 8, 337-354.
[PDF file]

Published in 1996


Hall, P. and Wand, M.P.
On the Accuracy of Binned Kernel Density Estimators.
Journal of Multivariate Analysis, 56, 165-184.
[PDF file]

Turlach, B.A. and Wand, M.P.
Fast Computation of Auxiliary Quantities in Local Polynomial Regression.
Journal of Computational and Graphical Statistics, 5, 337-350.
[PDF file]

González-Manteiga, W., Sánchez-Sellero, C. and Wand, M.P.
Accuracy of Binned Kernel Functional Approximations.
Computational Statistics and Data Analysis, 22, 1-16.
[PDF file]

Published in 1995


Ruppert, D., Sheather, S.J. and Wand, M.P.
An Effective Bandwidth Selector for Local Least Squares Regression.
Journal of the American Statistical Association, 90, 1257-1270.
[PDF file]

Fan, J., Heckman, N.E. and Wand, M.P.
Local Polynomial Kernel Regression for Generalized Linear Models and Quasi-Likelihood Functions.
Journal of the American Statistical Association, 90, 141-150.
[PDF file]

Herrmann, E., Engel, J., Wand, M.P. and Gasser, T.
A Bandwidth Selector for Bivariate Kernel Regression.
Journal of the Royal Statistical Society, Series B, 57, 171-180.
[PDF file]

Aldershof, B., Marron, J.S., Park, B.U. and Wand, M.P.
Facts About the Gaussian Probability Density Function.
Applicable Analysis, 59, 289-306.
[PDF file]

Published in 1994


Wand, M.P.
Fast Computation of Multivariate Kernel Estimators.
Journal of Computational and Graphical Statistics, 3, 433-445.
[PDF file]

Ruppert, D. and Wand, M.P.
Multivariate Locally Weighted Least Squares Regression.
The Annals of Statistics, 22, 1346-1370.
[PDF file]

Wand, M.P. and Jones, M.C.
Multivariate Plug-in Bandwidth Selection.
Computational Statistics, 9, 97-116.
[PDF file]

Published in 1993


Wand, M.P. and Jones, M.C.
Comparison of Smoothing Parameterizations in Bivariate Kernel Density Estimation.
Journal of the American Statistical Association, 88, 520-528.
[PDF file]

Devroye, L. and Wand, M.P.
On the Effect of Density Shape on the Performance of its Kernel Estimate.
Statistics, 24, 215-233.
[PDF file]

M.P. Wand and Devroye, L.
How Easy is a Given Density to Estimate?
Computational Statistics and Data Analysis, 16, 313-323.
[PDF file]

Published in 1992


Marron, J.S. and Wand, M.P.
Exact Mean Integrated Squared Error.
The Annals of Statistics, 20, 712-736.
[PDF file]

Wand, M.P.
Error Analysis for General Multivariate Kernel Estimators.
Journal of Nonparametric Statistics, 2, 1-15.
[PDF file]

Wand, M.P.
Finite Sample Performance of Density Estimators Under Moving Average Dependence.
Statistics and Probability Letters, 13, 109-115.
[PDF file]

Ruppert, D. and Wand, M.P.
Correcting for Kurtosis in Density Estimation.
Australian Journal of Statistics, 34, 19-29.
[PDF file]

Jones, M.C. and Wand, M.P.
Asymptotic Effectiveness of Some Higher Order Kernels.
Journal of Statistical Planning and Inference, 31, 15-21.
[PDF file]

Published in 1991


Wand, M.P., Marron, J.S. and Ruppert, D.
Transformations in Density Estimation (with discussion).
Journal of the American Statistical Association, 86, 343-361.
[PDF file]

Scott, D.W. and Wand, M.P.
Feasibility of Multivariate Density Estimates.
Biometrika, 78, 197-205.
[PDF file]

Carroll, R.J. and Wand, M.P.
Semiparametric Estimation in Logistic Measurement Error Models.
Journal of the Royal Statistical Society, Series B, 53, 573-585.
[PDF file]

Published in 1990


Wand, M.P.
On Exact L1 Rates of Convergence in Nonparametric Kernel Regression.
Scandinavian Journal of Statistics, 18, 197-204.
[PDF file]

Wand, M.P. and Schucany, W.R.
Gaussian-based Kernels.
Canadian Journal of Statistics, 18, 197-204.
[PDF file]

Härdle, W., Marron, J.S. and Wand, M.P.
Bandwidth Choice for Density Derivatives.
Journal of the Royal Statistical Society, Series B, 52, 223-232.
[PDF file]

Published in 1988


Hall, P. and Wand, M.P.
Minimizing L1Distance in Nonparametric Density Estimation.
Journal of Multivariate Analysis, 26, 59-88.
[PDF file]

Hall, P. and Wand, M.P.
Minimizing L1On Nonparametric Discrimination using Density Differences.
Biometrika, 75, 541-547.
[PDF file]

Hall, P. and Wand, M.P.
Minimizing L1On the Minimization of Absolute Distance in Kernel Density Estimation.
Statistics and Probability Letters, 6, 311-314.
[PDF file]