282 results found
Hand DJ, Hand DJ, 2012, Assessing the Performance of Classification Methods, INTERNATIONAL STATISTICAL REVIEW, Vol: 80, Pages: 400-414, ISSN: 0306-7734
Hand DJ, Hand DJ, 2012, An Introduction to Statistical Concepts, 3rd edition, INTERNATIONAL STATISTICAL REVIEW, Vol: 80, Pages: 489-491, ISSN: 0306-7734
Ross GJ, Adams NM, Tasoulis DK, et al., 2012, Exponentially weighted moving average charts for detecting concept drift, PATTERN RECOGNITION LETTERS, Vol: 33, Pages: 191-198, ISSN: 0167-8655
Ross GJ, Adams NM, Tasoulis DK, et al., 2012, Exponentially weighted moving average charts for detecting concept drift (vol 33, pg 191, 2012), PATTERN RECOGNITION LETTERS, Vol: 33, Pages: 2261-2261, ISSN: 0167-8655
A general method is formalised for the problem of making predictions for a fixed group of individual units, following a sequence of repeated measures on each. A review of some related work is undertaken and, using some of its terminology, the approach might be described as approximate non-parametric empirical Bayes prediction. It is contended that the method may often produce predictions that are, in practice, comparable or not much worse than more sophisticated methods, but sometimes for a smaller computational cost. Two examples are used to demonstrate the approach, exploring the prediction of baseball averages and spatial-temporal rainfall. The method performs favourably in both examples in comparison with James-Stein, empirical Bayes and other predictions; it also provides a relatively simple and computationally feasible way of determining whether it is worth modelling between-individual variability.
Hand DJ, 2011, Simultaneous Inference in Regression by Wei Liu, International Statistical Review, Vol: 79, Pages: 288-289
Hand DJ, 2011, Logistic Regression Models by Joseph M. Hilbe, International Statistical Review, Vol: 79, Pages: 287-288
Hand DJ, 2011, Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians by Ronald Christensen, Wesley Johnson, Adam Branscum, Timothy E. Hanson, International Statistical Review, Vol: 79, Pages: 285-286
Hand DJ, 2011, Measurements and their Uncertainties: A Practical Guide to Modern Error Analysis by Ifan G. Hughes, Thomas P. A. Hase, International Statistical Review, Vol: 79, Pages: 280-280
Hand DJ, 2011, Diagnostic Measurement: Theory, Methods, and Applications by André A. Rupp, Jonathan Templin, Robert A. Henson, International Statistical Review, Vol: 79, Pages: 135-136
Hand DJ, 2011, Charming Proofs: A Journey into Elegant Mathematics by Claudi Alsina, Roger B. Nelsen, International Statistical Review, Vol: 79, Pages: 122-122
Hand DJ, 2011, Statistical Inference: An Integrated Bayesian/Likelihood Approach by Murray Aitkin, International Statistical Review, Vol: 79, Pages: 121-121
Hand DJ, 2011, Linear Causal Modeling with Structural Equations by Stanley A. Mulaik, International Statistical Review, Vol: 79, Pages: 299-300
Hand DJ, 2011, Introduction to Psychometric Theory by Tenko Raykov, George A. Marcoulides, International Statistical Review, Vol: 79, Pages: 298-299
Hand DJ, 2011, The Best Writing on Mathematics 2011, The Best Writing on Mathematics 2011, Editors: Pitici, Publisher: Princeton University Press, Pages: 67-74, ISBN: 9781400839544
This book belongs on the shelf of anyone interested in where math has taken us--and where it is headed.
Hand DJ, Kalton G, Hand DJ, 2011, Discussion of "Bayesian Models and Methods in Public Policy and Government Settings" by S. E. Fienberg, STATISTICAL SCIENCE, Vol: 26, Pages: 227-234, ISSN: 0883-4237
Star-galaxy classification is one of the most fundamental data-processing tasks in survey astronomy and a critical starting point for the scientific exploitation of survey data. Star-galaxy classification for bright sources can be done with almost complete reliability, but for the numerous sources close to a survey's detection limit each image encodes only limited morphological information about the source. In this regime, from which many of the new scientific discoveries are likely to come, it is vital to utilize all the available information about a source, both from multiple measurements and from prior knowledge about the star and galaxy populations. This also makes it clear that it is more useful and realistic to provide classification probabilities than decisive classifications. All these desiderata can be met by adopting a Bayesian approach to star-galaxy classification, and we develop a very general formalism for doing so. An immediate implication of applying Bayes's theorem to this problem is that it is formally impossible to combine morphological measurements in different bands without using colour information as well; however, we develop several approximations that disregard colour information as much as possible. The resultant scheme is applied to data from the UKIRT Infrared Deep Sky Survey (UKIDSS) and tested by comparing the results to deep Sloan Digital Sky Survey (SDSS) Stripe 82 measurements of the same sources. The Bayesian classification probabilities obtained from the UKIDSS data agree well with the deep SDSS classifications both overall (a mismatch rate of 0.022 compared to 0.044 for the UKIDSS pipeline classifier) and close to the UKIDSS detection limit (a mismatch rate of 0.068 compared to 0.075 for the UKIDSS pipeline classifier). The Bayesian formalism developed here can be applied to improve the reliability of any star-galaxy classification schemes based on the measured values of morphology statistics alone. © 2011 The Authors Monthly
Krzanowski WJ, Hand DJ, Krzanowski WJ, et al., 2011, Testing the difference between two Kolmogorov-Smirnov values in the context of receiver operating characteristic curves, JOURNAL OF APPLIED STATISTICS, Vol: 38, Pages: 437-450, ISSN: 0266-4763
The maximum vertical distance between a receiver operating characteristic (ROC) curve and its chance diagonal is a common measure of effectiveness of the classifier that gives rise to this curve. This measure is known to be equivalent to a two-sample Kolmogorov--Smirnov statistic; so the absolute difference <italic>D</italic> between two such statistics is often used informally as a measure of difference between the corresponding classifiers. A significance test of <italic>D</italic> is of great practical interest, but the available Kolmogorov--Smirnov distribution theory precludes easy analytical construction of such a significance test. We, therefore, propose a Monte Carlo procedure for conducting the test, using the binormal model for the underlying ROC curves. We provide Splus/R routines for the computation, tabulate the results for a number of illustrative cases, apply the methods to some practical examples and discuss some implications.
Pavlidis NG, Tasoulis DK, Adams NM, et al., 2011, lambda-Perceptron: An adaptive classifier for data streams, PATTERN RECOGNITION, Vol: 44, Pages: 78-96, ISSN: 0031-3203
Adams NM, Tasoulis DK, Anagnostopoulos C, et al., 2010, Temporally-Adaptive Linear Classification for Handling Population Drift in Credit Scoring, 19th International Conference on Computational Statistics (COMPSTAT'2010), Publisher: PHYSICA-VERLAG GMBH & CO, Pages: 167-176
Anagnostopoulos C, Adams NM, Hand DJ, et al., 2010, Streaming Covariance Selection with Applications to Adaptive Querying in Sensor Networks, COMPUTER JOURNAL, Vol: 53, Pages: 1401-1414, ISSN: 0010-4620
Brentnall AR, Crowder MJ, Hand DJ, et al., 2010, Likelihood-ratio changepoint features for consumer-behaviour models, Conference on Credit Scoring and Credit Control X, Publisher: PALGRAVE MACMILLAN LTD, Pages: 462-472, ISSN: 0160-5682
Brentnall AR, Crowder MJ, Hand DJ, et al., 2010, Predicting the amount individuals withdraw at cash machines using a random effects multinomial model, STATISTICAL MODELLING, Vol: 10, Pages: 197-214, ISSN: 1471-082X
Brentnall AR, Crowder MJ, Hand DJ, et al., 2010, Predictive-sequential forecasting system development for cash machine stocking, INTERNATIONAL JOURNAL OF FORECASTING, Vol: 26, Pages: 764-776, ISSN: 0169-2070
The development of a system for predicting the daily amounts withdrawn from automated teller machines (ATMs) for inventory control is considered, using data from 190 ATMs in the United Kingdom over a two-year period. We argue that density forecasts are more appropriate than point forecasts and that a good forecasting system might choose a different model for each ATM. An analysis of the data finds that seasonal structure, first-order autocorrelation and cash-out days are important aspects of the data. Predictive sequential (prequential) comparisons between linear models, autoregressive models, structural time series models and Markov-switching models are made. The Markov-switching models are preferred because they are found to produce better density forecasts, and might also be more useful for inventory control because they separate the demand for cash from 'out-of-service' effects. A logarithmic scoring rule is used to choose the most appropriate seasonal and distributional assumptions for each ATM.
Hand DJ, 2010, The Oxford Handbook of Applied Bayesian Analysis edited by Anthony O’Hagan, Mike West, International Statistical Review, Vol: 78, Pages: 474-475
Hand DJ, 2010, Estimation and tests in distribution mixtures and change‐points models by Odile Pons, International Statistical Review, Vol: 78, Pages: 475-476
Hand DJ, 2010, Statistical Detection and Surveillance of Geographic Clusters, Journal of the Royal Statistical Society: Series A (Statistics in Society), Vol: 173, Pages: 937-938
Hand DJ, 2010, The Statistical Mind in Modern Society: The Netherlands 1850-1940: vol. 1, Official Statistics, Social Progress and Modern Enterprise; vol. 2, Statistics and Scientific Work, Journal of the Royal Statistical Society: Series A (Statistics in Society), Vol: 173, Pages: 936-937
Hand DJ, 2010, Modeling and Analysis of Stochastic Systems, Second Edition by Vidyadhar G. Kulkarni, International Statistical Review, Vol: 78, Pages: 467-467
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