Further information

Publications

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To Appear

• Arciniegas-Alarcon, S., Garcia-Pena, M., Krzanowski, W. J. and Rengifo, C Missing value imputation in a data matrix using the regularised singular value decomposition, MethodsX, pp 102289, vol. 11

2022

• Arciniegas-Alarcon, S., Garcia-Pena, M. and Krzanowski, W. J Cross-validation for lower rank matrices containing outliers, Applied System Innovation, pp 69, vol. 5(4)
• Bingham, N. H. and Krzanowski, W. J Linear algebra and multivariate analysis in statistics; development and interconnections in the twentieth century, British Journal for the History of Mathematics, pp 43-63, vol. 37
• Garcia-Pena, M., Arciniegas-Alarcon, S. and Krzanowski, W.J Missing value imputation using least squares techniques in contaminated matrices, MethodsX, pp 101683, vol. 9

2021

• Arciniegas-Alarcon, S., Garcia-Pena, M., Rengifo, C. and Krzanowski, W. J Techniques for robust imputation in incomplete two-way tables, Applied System Innovation, pp 62, vol. 4(3)
• Garcia-Pena, M., Arciniegas-Alarcon, S., Krzanowski, W.J. and Duarte, D. Missing-value imputation using the robust singular-value decomposition: proposals and numerical evaluation, Crop Science, pp 3288-3300, vol. 61
• Jakaite, L., Schetinin, V., Hladuvka, J., Minaev, S., Ambia, A. and Krzanowski, W Deep Learning for Early Detection of Pathological Changes in X-Ray Bone Micro-Structures: Case of Osteoarthritis, Scientific Reports, pp 2294, vol. 11

2020

• Arciniegas-Alarcon, S., Garcia-Pena, M. and Krzanowski, W.J Imputation using the singular value decomposition: variants of existing methods, proposed and assessed, International Journal of Innovative Computing, Information and Control, pp 1681-1696, vol. 16

2018

• Schetinin, V., Jackaite, L. and Krzanowski, W.J Bayesian averaging over Decision Tree models for trauma severity scoring, Artificial Intelligence in Medicine, pp 139-145, vol. 84
• Schetinin, V., Jakaite, L. and Krzanowski, W.J Bayesian averaging over Decision Tree models: an application for estimating uncertainty in Trauma Severity scoring, International Journal of Medical Informatics, pp 6-14, vol. 112
• Schetinin, V., Jakaite, L., Nyah, N., Novakovic, D. and Krzanowski, W.J Feature extraction with GMDH-type Neural Networks for EEG-based person identification, International Journal of Neural Systems, vol. 28 (6)
• Schetinin, V., Jakaite, L., and Krzanowski, W.J. Bayesian Learning of Models for Estimating Uncertainty in Alert Systems: Application to Aircraft Collision Avoidance, Integrated Computer-Aided Engineering, pp 229-245, vol. 25

2016

• Arciniegas-Alarcon, S., Garcia-Pena, M. and Krzanowski, W.J Missing value imputation in multi-environmental trials: reconsidering the Krzanowski method, Crop Breeding and Applied Biotechnology, pp 77-85, vol. 16
• Garcia-Pena, M., Arcinegas-Alarcon, S., Krzanowski, W.J. and Barbin, D Multiple imputation procedures using the GabrielEigen algorithm, Communications in Biometry and Crop Science, pp 149-163, vol. 11

2015

• Kozak, M., Krzanowski, W.J., Cichocka, I. and Hartley, J The effects of data input errors on subsequent statistical inference, Journal of Applied Statistics, pp 2030-2037, vol. 42

2014

• Arciniegas-Alarcon, S., Garcia-Pena, M., Krzanowski, W.J. and Dias, C. T. dos S An alternative methodology for imputing missing data in trials with genotype-by-environment interaction: some new aspects, Biometrical Letters, pp 75-88, vol. 51
• Arciniegas-Alarcón, S., García-Peña, M., Krzanowski, W.J. and Dias, C.T. dos S Imputing missing values in multi-environment trials using the singular value decomposition: An empirical comparison, Communications in Biometry and Crop Science, pp 54-70, vol. 9(2)

2013

• Arciniegas-Alarcon, S., Garcia-Pena, M., Krzanowski, W.J. and Dias, C.T. dos S Deterministic imputation in multienvironment trials, ISRN Agronomy, pp 17, vol. 2013
• Schetinin, V., Jakaite, L. and Krzanowski, W.J Prediction of survival probabilities with Bayes decision trees, Expert Systems with Applications, pp 5466-5476, vol. 40
• Schetinin, V., Jakaite, L., Jakaitis, J. and Krzanowski, W.J Bayesian decision trees for predicting survival of patients: a study on the US national trauma data bank, Computer Methods and Programs in Biomedicine, pp 602-612, vol. 111
• Trendafilov, N.T., Unkel, S. and Krzanowski, W.J Exploratory factor and principal component analyses: some new aspects, Statistics and Computing, pp 209-220, vol. 23

2012

• Bailey, T.C. and Krzanowski, W.J An overview of approaches to the analysis and modelling of multivariate geostatistical data, Mathematical Geosciences, pp 381-393, vol. 44
• Kozak, M. and Krzanowski, W.J On using the h-index to analyse species biodiversity and other count data, Current Science, pp 9, vol. 103
• Kozak, M., Krzanowski, W.J. and Tartanus, M Use of the correlation coefficient in agricultural sciences: problems, pitfalls and how to deal with them, Anais da Academia Brasileira de Ciencias, pp 1147-1156, vol. 84

2011

• Kozak, M., Azevedo, R.A., Jupowicz-Kozak, J. and Krzanowski, W.J Reporting numbers in agriculture and biology: Don`t overdo the digits, Australian J. of Crop Science, pp 1876-1881, vol. 5
• Krzanowski, W.J. and Hand, D.J. Testing the difference between two Kolmogorov-Smirnov values in the context of Receiver Operating Characteristic curves, Journal of Applied Statistics, pp 437-450, vol. 38

2010

• Arciniegas-Alarcon, S., Garcia-Pena, M., Dias, C.T. dos S. and Krzanowski, W.J. An alternative methodology for imputing missing data in trials with genotype-by-environment interaction, Biometrical Letters, pp 1-14, vol. 47
• Kozak, M. and Krzanowski, W.J Effective presentation of data, European Science Editing, pp 41-42, vol. 36
• Kozak, M., Wnuk, A. and Krzanowski, W.J A simple R function for inspecting multivariate data, Communications in Biometry and Crop Science, pp 34-40, vol. 5

2009

• Bailey, T.C. and Krzanowski, W.J Structuring Complex Correlations: An Overview of Multivariate Spatial Approaches, Proceedings of the 57th sesssion of the International Statistical Institute, Durban, South Africa
• Krzanowski, W.J. and Hand, D.J A simple method for screening variables before clustering microarray data, Computational Statistics and Data Analysis, pp 2747-2753, vol. 53
• Krzanowski, W.J. and Hand, D.J ROC Curves for Continuous Data, Chapman and Hall/CRC
• Mahat, N.I., Krzanowski, W.J. and Hernandez, A Strategies for non-parametric smoothing of the location model in mixed-variable discriminant analysis, Modern Applied Science, pp 151-163, vol. 3

2008

• Bergamo, G.C., Dias, C.T. dos S. and Krzanowski, W.J. Distribution-free multiple imputation in an interaction matrix, using the singular value decomposition, Scientia Agricola, pp 422-427, vol. 65
• Kim, S-S., Park, S.H. and Krzanowski, W.J Simultaneous variable selection and outlier identification in linear regression using the mean-shift outlier model, Journal of Applied Statistics, pp 283-291, vol. 35

2007

• Krzanowski, W.J. and Bailey, T.C. Extraction of spatial features using factor methods, illustrated on stream sediment data, Mathematical Geology, pp 69-85, vol. 39 (1)
• Schetinin, V., Fieldsend, J.E., Partridge, D., Coats, T.J., Krzanowski, W.J., Everson, R.M., Bailey, T.C., Hernandez, A Confident Interpretation of Bayesian Decision Tree Ensembles for Clinical Applications, IEEE Transactions on Information Technology in Biomedicine, pp 312-319, vol. 11
• Bailey, T.C., Everson, R.M., Fieldsend, J.E., Krzanowski, W.J., Partridge, D., Schetinin, V Representing classifier confidence in the safety critical domain --- an illustration from mortality prediction in trauma cases, Neural Computing and Applications, pp 1-10, vol. 16
• Crowder, M.J., Hand, D.J. and Krzanowski, W.J On optimal intervention for customer lifetime value, European Journal of Operational Research, pp 1550-1559, vol. 183
• Hand, D.J., Krzanowski, W.J. and Crowder, M.J Optimal predictive partitioning, Statistics and Computing, pp 11-21, vol. 17
• Kim, S.S. and Krzanowski, W.J Detecting multiple outliers in linear regression using a cluster method combined with graphical visualisation, Computational Statistics, pp 109-119, vol. 22
• Krzanowski, W.J Statistical Principles and Techniques in Scientific and Social Research, Oxford University Press, pp 241 + xiv
• Krzanowski, W.J. and Hand, D.J A recursive partitioning tool for interval prediction, Advances in Data Analysis and Classification, pp 241-254, vol. 1
• Mahat, N.I., Krzanowski, W.J. and Hernandez, A. Variable selection in discriminant analysis based on the location model for mixed variables, Advances in Data Analysis and Classification, pp 105-122, vol. 1
• Schetinin, V., Fieldsend, J.E., Partridge, D., Krzanowski, W.J., Everson, R.M., Bailey, T.C., Hernandez, A Estimating Classification Uncertainty of Bayesian Decision Tree Techniques on Financial Data, Batyrshin, I., Kacprzyk, J., Sheremetov, L., Zadeh, L.A. (Eds), Perception-based Data Mining and Decision Making in Economics and Finance. Series: Studies in Computational Intelligence, pp 155-179, vol. 36
• Schetinin, V., Fieldsend, J.E., Partridge, D., Krzanowski, W.J., Everson, R.M., Bailey, T.C., Hernandez, A Comparison of the Bayesian and Randomised Decision Tree Ensembles within an Uncertainty Envelope Technique, Journal of Mathematical Modelling and Algorithms, pp 397-416, vol. 5 (4)
• Schetinin, V., Krzanowski, W.J. and Maple, C The Bayesian decision tree technique using an adaptive sampling scheme, Twentieth IEEE International Symposium on Computer-based Medical Systems (CBMS 07), pp 121-126

2006

• Krzanowski, W.J., Fieldsend, J.E., Bailey, T.C., Everson, R.M., Partridge, D., Schetinin, V Confidence in classification: a Bayesian approach, Journal of Classification, pp 199-220, vol. 23
• Dias, C.T. dos S. and Krzanowski, W.J Choosing components in the additive main effect and multiplicative interaction (AMMI) models, Scientia Agricola, pp 169-175, vol. 63
• Everson, R., Fieldsend, J., Bailey, T., Krzanowski, W., Partridge, D., Hernandez, A., Schetinin, V Optimising Data-Driven Safety Related Systems, Developments in Risk-based Approaches to Safety, Proceedings of the Fourteenth Safety-critical Systems Symposium, Bristol, UK, pp 217-230
• Krzanowski, W.J Sensitivity in metric scaling and analysis of distance, Biometrics, pp 239-244, vol. 62
• Partridge, D., Bailey, T., Everson, R., Fieldsend, J., Hernandez, A., Krzanowski, W., Schetinin, V Classification with Confidence for Critical Systems, Developments in Risk-based Approaches to Safety, Proceedings of the Fourteenth Safety-critical Systems Symposium, Bristol, UK, pp 231-240
• Partridge, D., Fieldsend, J.E., Krzanowski, W., Bailey, T.C., Everson, R.M., Schetinin, V Computing with confidence: a Bayesian approach, Proceedings of Internet, Processing, Systems, and Interdisciplinary (Research) Conference (IPSI-2006), April 27-30th, Carcassonne, France
• Partridge, D., Schetinin, V., Li, D., Coats, T.J., Fieldsend, J.E., Krzanowski, W.J., Everson, R.M., Bailey, T.C Interpretability of Bayesian Decision Trees Induced from Trauma Data, L. Rutkowski, R. Tadeusiewicz, L. A. Zadeh, J. Zurada (Eds), Lecture Notes in Artificial Intelligence, LNAI 4029. Springer, pp 972-981
• Schetinin, V., Fieldsend, J.E., Partridge, D., Krzanowski, W.J., Everson, R.M., Bailey, T.C., Hernandez, A A Bayesian Methodology for Estimating Uncertainty of Decisions in Safety-Critical Systems, Xuan F Zha and R.J. Howlett (Eds), "Integrated Intelligent Systems for Engineering Design", IOS Press, pp 82-96, vol. 149

2005

• Turner, H., Bailey, T.C. and Krzanowski, W.J Improved biclustering of microarray data demonstrated through systematic performance tests, Computational Statistics and Data Analysis, pp 235-254, vol. 48 (2)
• Bailey, T.C., Barcellos, C. and Krzanowski, W.J Use of spatial factors in the analysis of heavy metals in sediments in a Brazillian coastal region, Environmetrics, pp 563-572, vol. 16 (6)
• Hand, D.J. and Krzanowski, W.J Optimising k-means clustering results with standard software packages, Computational Statistics and Data Analysis, pp 969-973, vol. 49
• Turner, H., Bailey, T.C., Krzanowski, W.J. and Hemingway, C Biclustering models for structured microarray data, IEEE/ACM Transactions on Computational Biology and Bioinformatics, pp 316-329, vol. 2 (4)

2004

• Badcock, J., Bailey, T.C., Krzanowski, W.J. and Jonathan, P Two projection methods for use in the analysis of multivariate process data, with an illustration in petrochemical production, Technometrics, pp 392-403, vol. 46
• Ahmed, S.E. and Krzanowski, W.J Biased estimation in a simple multivariate regression model, Computational Statistics and Data Analysis, pp 689-696, vol. 45
• Andrade, J.M., Gomez-Carracedo, M., Krzanowski, W.J. and Kubista, M Procrustes rotation in analytical chemistry: a tutorial, Chemometrics & Intelligent Laboratory Systems, pp 123-132, vol. 72
• Krzanowski, W.J Biplots for multifactorial analysis of distance, Biometrics, pp 517-524, vol. 60
• Schetinin, V., Fieldsend, J.E., Partridge, D., Krzanowski, W.J., Everson, R.M., Bailey, T.C., Hernandez, A The Bayesian Decision Tree Technique with a Sweeping Strategy, AISTA 2004, 2004 International Conference on Advances in Intelligent Systems - Theory and Applications In cooperation with the IEEE Computer Society, November 15-18, 2004, Centre de Recherche Public Henri Tudor, Luxembourg-Kirchberg, Luxembourg
• Schetinin, V., Partridge, D., Krzanowski, W.J., Everson, R.M., Fieldsend, J.E., Bailey, T.C., Hernandez, A Experimental Comparison of Classification Uncertainty for Randomised and Bayesian Decision Tree Ensembles, Proceedings of the Fifth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'04), Lecture Notes in Computer Science (LNCS 3177), Z.R. Yang, R. Everson and H. Yin (Eds.), Exeter, August 25-27, Springer, pp 726-732

2003

• Bolton, R.J. and Krzanowski, W.J. Projection pursuit clustering for exploratory data analysis, Journal of Computational and Graphical Statistics, pp 121-142, vol. 12
• Dias, C.T. dos S. and Krzanowski, W.J Model selection and cross-validation in additive main effect and multiplicative interaction (AMMI) models, Crop Science, pp 865-873, vol. 43
• Fieldsend, J.E., Bailey, T.C., Everson, R.M., Krzanowski, W.J., Partridge, D., Schetinin, V Bayesian inductively learned modules for safety critical systems, Proceedings of the 35th Symposium on the Interface: Computing Science and Statistics. March 12-15, Salt Lake City, pp 110-125 [Data]
• Krzanowski, W.J Orthogonal components for grouped data: review and applications, Statistics in Transition, pp 759-777, vol. 5
• Krzanowski, W.J Nonparametric estimation of distances between groups, Journal of Applied Statistics, pp 743-750, vol. 30

2002

• Collins, G.S. and Krzanowski, W.J. Nonparametric discriminant analysis of phytoplankton species using data from analytical flow cytometry, Cytometry, pp 26-33, vol. 48
• Krzanowski, W.J Multifactorial analysis of distance in studies of ecological community structure, Journal of Agricultural, Biological and Environmental Statistics, pp 222-232, vol. 7

2001

• Asparoukhov, O. and Krzanowski, W.J A comparison of discriminant procedures for binary variables, Computational Statistics and Data Analysis, pp 139-60, vol. 38 (2)
• Badcock, J., Bailey, T.C. and Krzanowski, W.J. Modelling of multivariate process control data, In: New Trends in Statistical Modelling: Proceedings of the 16th International Workshop on Statistical Modelling, B. Klein & L.Korsholm (eds), University of Southern Denmark, pp 409-412
• Krzanowski, W.J Data-based interval estimation of classification error rates, Journal of Applied Statistics, pp 585-95, vol. 28 (5)

2000

• Asparoukhov, O. and Krzanowski, W.J Non-parametric smoothing of the location model in mixed variable discrimination, Statistics and Computing, pp 285-293, vol. 10
• Bailey. T.C. and Krzanowski, W.J Extensions to Spatial Factor Methods with an Illustration in Geochemistry, Mathematical Geology, pp 657-682, vol. 32 (6)
• Jonathan, P., Krzanowski, W.J. and McCarthy, W.V On the use of cross-validation to assess performance in multivariate prediction, Statistics and Computing, pp 209-229, vol. 10
• Kiers, H.A.L. and Krzanowski, W.J Projections distinguishing isolated groups in multivariate data spaces, In: Data analysis: Scientific modeling and practical application (W. Gaul, O. Opitz, & M. Schader, eds.), Heidelberg: Springer, pp 207-218
• Krzanowski, W.J Principles of Multivariate Analysis: a User's Perspective (Revised Edition), Oxford University Press, pp 586 + xxi

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