3 Large sample approximations and asymptotic expansions of classification statistics

Publisher Summary The distributions of classification statistics are needed mainly to know the Probability of Misclassification (PMC) or the probability of Correct Classification (PCC), an optimum choice of cut-off point, and to discuss on some testing hypotheses and estimations in the classification. Unfortunately, the exact distributions are usually hard to obtain. In the non-parametric classification, the distribution of classification statistics is usually based on the large samples. This chapter considers the distributions of classification statistics, such as statistics for classification of one of two multivariate normal populations with a common covariance matrix, statistics of classification into one of the two multivariate normal populations with different covariance matrices, and statistics in the non-normal case and in the discrete case.

[1]  Day Ne,et al.  A GENERAL MAXIMUM LIKELIHOOD DISCRIMINANT , 1967 .

[2]  William G. Cochran,et al.  Comparison of two methods of handling covariates in discriminatory analysis , 1964 .

[3]  Peter A. Lachenbruch,et al.  Robustness of the linear and quadratic discriminant function to certain types of non‐normality , 1973 .

[4]  M Goldstein An Appropriate Test For Comparative Discriminatory Power. , 1976, Multivariate behavioral research.

[5]  A. Wald On a Statistical Problem Arising in the Classification of an Individual into One of Two Groups , 1944 .

[6]  C. A. Smith Some examples of discrimination. , 1947, Annals of eugenics.

[7]  J. Anderson Separate sample logistic discrimination , 1972 .

[8]  M. Hills,et al.  Discrimination and Allocation with Discrete Data , 1967 .

[9]  Matthew Goldstein,et al.  Selection of Variates for the Two-Group Multinomial Classification Problem , 1975 .

[10]  M. Hills Allocation Rules and Their Error Rates , 1966 .

[11]  S. Kullback,et al.  AN APPLICATION OF INFORMATION THEORY TO MULTIVARIATE ANALYSIS, II , 1952 .

[12]  H. Linhart,et al.  Zur Wahl von Variablen in der Trennanalyse , 1961 .

[13]  J. Wise,et al.  THE AUTOCORRELATION FUNCTION AND THE SPECTRAL DENSITY FUNCTION , 1955 .

[14]  Calyampudi R. Rao A General Theory of Discrimination When the Information About Alternative Population Distributions is Based on Samples , 1954 .

[15]  K. Matusita Classification based on distance in multivariate Gaussian cases , 1967 .

[16]  P. Lachenbruch Discriminant Analysis When the Initial Samples Are Misclassified , 1966 .

[17]  G. McLachlan Asymptotic Results for Discriminant Analysis When the Initial Samples are Misclassified , 1972 .

[18]  Wojtek J. Krzanowski,et al.  Discrimination and Classification Using Both Binary and Continuous Variables , 1975 .

[19]  Ingram Olkin,et al.  Multivariate Correlation Models with Mixed Discrete and Continuous Variables , 1961 .

[20]  J. Neyman,et al.  Research Papers in Statistics. Festschrift for J. Neyman F.N. David editor, assisted by E. Fix. London, New York, Sydney, J. Wiley & Sons, 1966, VIII p. 468 p., 105/–. , 1968, Recherches économiques de Louvain.

[21]  Chien-Pai Han,et al.  A note on discrimination in the case of unequal covariance matrices , 1968 .

[22]  M. Okamoto An Asymptotic Expansion for the Distribution of the Linear Discriminant Function , 1963 .

[23]  G. McLachlan An Asymptotic Unbiased Technique for Estimating the Error Rates in Discriminant Analysis , 1974 .

[24]  Masashi Okamoto,et al.  Asymptotic expansion of the distribution of the Z statistic in discriminant analysis , 1971 .

[25]  T. W. Anderson,et al.  Classification into two Multivariate Normal Distributions with Different Covariance Matrices , 1962 .

[26]  N. Glick Sample-Based Multinomial Classification , 1973 .

[27]  G. McLachlan AN ASYMPTOTIC EXPANSION OF THE EXPECTATION OF THE ESTIMATED ERROR RATE IN DISCRIMINANT ANALYSIS1 , 1973 .

[28]  Masashi Okamoto,et al.  The Classification Statistic $W^\ast$ in Covariate Discriminant Analysis , 1970 .

[29]  Geoffrey J. McLachlan,et al.  Constrained sample discrimination with the studentized classification statistic w , 1977 .

[30]  S. John,et al.  On classification by the statisticsR andZ , 1962 .

[31]  A. W. Davis,et al.  Generalized Asymptotic Expansions of Cornish-Fisher Type , 1968 .

[32]  Paul W. Cooper,et al.  The Hypersphere in Pattern Recognition , 1962, Inf. Control..

[33]  Wojtek J. Krzanowski,et al.  Canonical Representation of the Location Model for Discrimination or Classification , 1976 .

[34]  Masashi Okamoto,et al.  Discrimination for variance matrices , 1961 .

[35]  R. Fisher THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .

[36]  R. Kronmal,et al.  The Estimation of Probability Densities and Cumulatives by Fourier Series Methods , 1968 .

[37]  M. R. Mickey,et al.  Estimation of Error Rates in Discriminant Analysis , 1968 .

[38]  P. Patnaik THE NON-CENTRAL χ2- AND F-DISTRIBUTIONS AND THEIR APPLICATIONS , 1949 .

[39]  N. Glick Sample-Based Classification Procedures Derived from Density Estimators , 1972 .

[40]  Yasunori Fujikoshi,et al.  THE DISTRIBUTION OF THE STUDENTIZED CLASSIFICATION STATISTIC W* IN COVARIATE DISCRIMINANT ANALYSIS , 1977 .

[41]  T. W. Anderson Asymptotic Evaluation of the Probabilities of Misclassification by Linear Discriminant Functions , 1973 .

[42]  K. Matusita Decision rule, based on the distance, for the classification problem , 1956 .

[43]  K. S. Banerjee,et al.  Bounds in a minimax classification procedure , 1965 .

[44]  M Goldstein,et al.  A Two-Group Classification Procedure For Multivariate Dichotomous Responses. , 1977, Multivariate behavioral research.

[45]  R. H. Riffenburgh,et al.  Geometry and linear discrimination , 1960 .

[46]  E. S. Gilbert On Discrimination Using Qualitative Variables , 1968 .

[47]  T. W. Anderson Classification by multivariate analysis , 1951 .

[48]  T. W. Anderson,et al.  An Introduction to Multivariate Statistical Analysis , 1959 .

[49]  Ahmed Zogo Memon Z statistic in discriminant analysis , 1968 .

[50]  P. Cooper Statistical classification with quadratic forms , 1963 .

[51]  Chien-Pai Han,et al.  Distribution of Discriminant Function When Covariance Matrices are Proportional , 1969 .

[52]  Abdelmonem A. Afifi,et al.  Classification Based on Dichotomous and Continuous Variables , 1974 .

[53]  W. G. Cochran,et al.  Discriminant Functions with Covariance , 1948 .

[54]  H. D. Friedman On the expected error in the probability of misclassification , 1965 .

[55]  Mitsuyo Kanazawa,et al.  THE ASYMPTOTIC CUT-OFF POINT AND COMPARISON OF ERROR PROBABILITIES IN COVARIATE DISCRIMINANT ANALYSIS , 1979 .

[56]  William R. Dillon,et al.  On the Performance of Some Multinomial Classification Rules , 1978 .

[57]  W. G. Cochran,et al.  Some Classification Problems with Multivariate Qualitative Data , 1961 .

[58]  R. Kronmal,et al.  Some Classification Procedures for Multivariate Binary Data Using Orthogonal Functions , 1976 .

[59]  M. Bartlett,et al.  Discrimination in the case of zero mean differences , 1963 .

[60]  R. A. Bradley,et al.  Probability models, estimation, and classification for multivariate dichotomous populations. , 1972, Biometrics.

[61]  M. Okamoto Correction Notes: Correction to "An Asymptotic Expansion for the Distribution of the Linear Discriminant Function" , 1968 .

[62]  G. McLachlan The asymptotic distributions of the conditional error rate and risk in discriminant analysis , 1974 .

[63]  A. Kudô THE CLASSIFICATORY PROBLEM VIEWED AS A TWO-DECISION PROBLEM , 1959 .

[64]  Paul W. Cooper,et al.  Quadratic discriminant functions in pattern recognition (Corresp.) , 1965, IEEE Trans. Inf. Theory.

[65]  G. McLachlan The bias of the apparent error rate in discriminant analysis , 1976 .

[66]  S. Gupta THEORIES AND METHODS IN CLASSIFICATION: A REVIEW , 1973 .

[67]  G. McLachlan The relationship in terms of asymptotic mean square error between the separate problems of estimating each of the three types of error rate of the linear discriminant function , 1974 .

[68]  T. W. Anderson An Asymptotic Expansion of the Distribution of the Studentized Classification Statistic $W^1$ , 1973 .

[69]  Solomon Kullback,et al.  Information Theory and Statistics , 1960 .

[70]  D. Moore Evaluation of Five Discrimination Procedures for Binary Variables , 1973 .

[71]  N. L. Johnson,et al.  Systems of frequency curves generated by methods of translation. , 1949, Biometrika.

[72]  S. Gupta OPTIMUM CLASSIFICATION RULES FOR CLASSIFICATION INTO TWO MULTIVARIATE NORMAL POPULATIONS , 1965 .

[73]  A. Bowker,et al.  AN ASYMPTOTIC EXPANSION FOR THE DISTRIBUTION FUNCTION OF THE CLASSIFICATION STATISTIC W , 1959 .

[74]  D. Cox The Analysis of Multivariate Binary Data , 1972 .

[75]  C. Han,et al.  Distribution of discriminant function in circular models , 1970 .

[76]  G. McLachlan Estimation of the Errors of Misclassification on the Criterion of Asymptotic Mean Square Error , 1974 .

[77]  W. Krzanowski The Performance of Fisher's Linear Discriminant Function Under Non-Optimal Conditions , 1977 .