Maximum Likelihood Estimation of the Multivariate Normal Mixture Model
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[1] M. Kenward,et al. An Introduction to the Bootstrap , 2007 .
[2] J. Behboodian. Information matrix for a mixture of two normal distributions , 1972 .
[3] Michael I. Jordan,et al. On Convergence Properties of the EM Algorithm for Gaussian Mixtures , 1996, Neural Computation.
[4] P. J. Huber. The behavior of maximum likelihood estimates under nonstandard conditions , 1967 .
[5] J. MacKinnon,et al. Econometric Theory and Methods , 2003 .
[6] J. Horowitz. Bootstrap-based critical values for the information matrix test , 1994 .
[7] T. Louis. Finding the Observed Information Matrix When Using the EM Algorithm , 1982 .
[8] Dankmar Böhning,et al. Statistical Inference Based on a General Model of Unobserved Heterogeneity , 1995 .
[9] N. E. Day. Estimating the components of a mixture of normal distributions , 1969 .
[10] J. Habbema. A stepwise discriminant analysis program using density estimetion , 1974 .
[11] H. White. Maximum Likelihood Estimation of Misspecified Models , 1982 .
[12] J. Magnus,et al. Matrix Differential Calculus with Applications in Statistics and Econometrics (Revised Edition) , 1999 .
[13] D. Rubin,et al. Estimation and Hypothesis Testing in Finite Mixture Models , 1985 .
[14] K. Pearson. Contributions to the Mathematical Theory of Evolution , 1894 .
[15] Geoffrey J. McLachlan,et al. Standard errors of fitted component means of normal mixtures , 1997 .
[16] Peter Adams,et al. The EMMIX software for the fitting of mixtures of normal and t-components , 1999 .
[17] Andrew Chesher,et al. The information matrix test: Simplified calculation via a score test interpretation , 1983 .
[18] R. Fisher. THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .
[19] R. Hathaway. A Constrained Formulation of Maximum-Likelihood Estimation for Normal Mixture Distributions , 1985 .
[20] Geoffrey J. McLachlan,et al. Mixture models : inference and applications to clustering , 1989 .
[21] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[22] S. Newcomb. A Generalized Theory of the Combination of Observations so as to Obtain the Best Result , 1886 .
[23] Stephen M. Stigler. The History of Statistics: The Measurement of Uncertainty before 1900 , 1986 .
[24] A. F. Smith,et al. Statistical analysis of finite mixture distributions , 1986 .
[25] M. Newton. Approximate Bayesian-inference With the Weighted Likelihood Bootstrap , 1994 .
[26] J. Magnus,et al. Matrix Differential Calculus with Applications in Statistics and Econometrics , 1991 .
[27] Saralees Nadarajah,et al. Information matrices for normal and Laplace mixtures , 2007, Inf. Sci..
[28] S. Stigler,et al. The History of Statistics: The Measurement of Uncertainty before 1900 , 1986 .
[29] G. McLachlan,et al. The EM algorithm and extensions , 1996 .
[30] David Hinkley,et al. Bootstrap Methods: Another Look at the Jackknife , 2008 .
[31] Chuanhai Liu,et al. Information matrix computation from conditional information via normal approximation , 1998 .
[32] Geoffrey J. McLachlan,et al. Finite Mixture Models , 2019, Annual Review of Statistics and Its Application.
[33] Tony Lancaster,et al. THE COVARIANCE MATRIX OF THE INFORMATION MATRIX TEST , 1984 .