RUS  ENG JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PERSONAL OFFICE
 
Kagan Abram Meerovich

Statistics Math-Net.Ru
Total publications: 41
Scientific articles: 39

Number of views:
This page:401
Abstract pages:3798
Full texts:1415
References:117
Doctor of physico-mathematical sciences (1967)
E-mail:
Website: http://www.math.umd.edu/~amk/

Subject:

Parameter Estimation
Fisher Information
Characterization Problems
Sufficiency and Exponential Families
Generalized Linear Models

   
Main publications:
  • 2007
  • 1. Sub- and superadditivity a la Carlen of matrices related to the Fisher information (with Z. Landsman and C. R. Rao). J. Statist. Planning and Inference, 137, 291-298.
    2. A lemma on stochastic majorization and properties of the Student distribution (with A. V. Nagaev). Theory Probab. Applications, 52, no. 1.
    3. Strong decomposition of random variables (with J. Hoffman ?Jorgensen, L. Pitt and L. Shepp) J. Theoret. Probab.
    4. An identity for the Fisher information and Mahalanobis distance (with Bing Li) (submitted).
  • 2006
  • 1. Quasi-independence of random variables and a property of normal and gamma distributions. J. Statist. Planning and Inference, 136, 199-208.
    2. Profile sufficiency . Austrian J. Statistics, 35, 121-130.

http://www.mathnet.ru/eng/person30497
List of publications on Google Scholar
List of publications on ZentralBlatt
https://mathscinet.ams.org/mathscinet/MRAuthorID/96710

Publications in Math-Net.Ru
1. Contribution to the theory of Pitman estimators
A. M. Kagan, Tinghui Yu, A. Barron, M. Madiman
Zap. Nauchn. Sem. POMI, 408 (2012),  245–267
2. A lemma on stochastic majorization and properties of the Student distribution
A. M. Kagan, A. V. Nagaev
Teor. Veroyatnost. i Primenen., 52:1 (2007),  199–203
3. On estimation of a location parameter in presence of an ancillary component
A. M. Kagan, C. R. Rao
Teor. Veroyatnost. i Primenen., 50:1 (2005),  172–176
4. The least squares estimate, nonquadratic errors and the Gaussian distribution
A. A. Zinger, A. M. Kagan
Teor. Veroyatnost. i Primenen., 36:1 (1991),  34–41
5. Generalized Condition ot the Identity of Distributions of Random Vectors in Connection with the Asymptotic Theory of Linear Forms in Independent Random Values
A. M. Kagan
Teor. Veroyatnost. i Primenen., 34:2 (1989),  370–375
6. New Classes of Dependent Random Variables and Generalization of Darmois–Skytovich Theorem to the Case of Several Forms
A. M. Kagan
Teor. Veroyatnost. i Primenen., 33:2 (1988),  305–314
7. The analytical precising of the Heyde theorem on linear forms of independent random variables
A. M. Kagan
Zap. Nauchn. Sem. LOMI, 166 (1988),  54–59
8. A class of Two-Dimensional Distributions Arising in Connection with Cramer and Darmois–Skitovitch Theorems
A. M. Kagan
Teor. Veroyatnost. i Primenen., 32:2 (1987),  349–351
9. Contribution to the analytic theory of linear forms of independent random variables
A. A. Zinger, A. M. Kagan
Zap. Nauchn. Sem. LOMI, 153 (1986),  37–44
10. An information property of exponential families
A. M. Kagan
Teor. Veroyatnost. i Primenen., 30:4 (1985),  783–786
11. A simple modification of Pitman estimates for a location parameter
A. M. Kagan
Teor. Veroyatnost. i Primenen., 30:3 (1985),  562–566
12. Fisher Information Contained in a Finite-Dimensional Linear Space, and a Correctly Posed Version of the Method of Moments
A. M. Kagan
Probl. Peredachi Inf., 12:2 (1976),  20–42
13. A note on the problem of reconstructing the type of a distribution
A. A. Zinger, A. M. Kagan
Teor. Veroyatnost. i Primenen., 21:2 (1976),  398–401
14. Estimating stability in the problem of reconstructing the additive type of a distribution
A. M. Kagan, L. B. Klebanov
Zap. Nauchn. Sem. LOMI, 61 (1976),  68–74
15. Some wide-sense analogs of characteristic properties of the normal distribution
A. M. Kagan
Zap. Nauchn. Sem. LOMI, 61 (1976),  59–67
16. Hilbert space methods in classical problems of mathematical statistics
O. V. Gerleyn, A. M. Kagan
Zap. Nauchn. Sem. LOMI, 53 (1975),  64–100
17. Asymptotic behaviour of the polynomial Pitman estimators
A. M. Kagan, L. B. Klebanov, S. M. Fintushal
Zap. Nauchn. Sem. LOMI, 43 (1974),  30–39
18. Sample mean as an estimator of the location parameter in case of the Laplacian loss function, in presence of the nuisance scale parameter
A. A. Zinger, A. M. Kagan
Zap. Nauchn. Sem. LOMI, 43 (1974),  15–29
19. Bayes formulation of the location parameter estimation problem
A. M. Kagan, Yu. N. Karpov
Zap. Nauchn. Sem. LOMI, 29 (1972),  62–73
20. Families with “self-control”
A. M. Kagan, Yu. V. Linnik, J. V. Romanovsky, A. L. Rukhin
Dokl. Akad. Nauk SSSR, 199:4 (1971),  766–769
21. The sample mean as an estimator of the shift parameter in the presence of certain losses which differ from the quadratic
A. A. Zinger, A. M. Kagan, L. B. Klebanov
Dokl. Akad. Nauk SSSR, 189:1 (1969),  29–30
22. Admissibility of the estimate of least squares. Unusual property of the normal law
A. M. Kagan, O. V. Shalaevskii
Mat. Zametki, 6:1 (1969),  81–89
23. Theory of estimation for families with shift, scale and exponential parameters
A. M. Kagan
Trudy Mat. Inst. Steklov., 104 (1968),  19–87
24. Conditions of optimal unbiased estimation of parametric functions for incomplete exponential families with polynomial constraints
A. M. Kagan, V. P. Palamodov
Dokl. Akad. Nauk SSSR, 175:6 (1967),  1216–1218
25. Partial sufficiency and unbiased estimation of polynomials in the shift parameter
A. M. Kagan
Dokl. Akad. Nauk SSSR, 174:6 (1967),  1257–1259
26. On the estimation theory of the scale parameter
A. M. Kagan, A. L. Rukhin
Teor. Veroyatnost. i Primenen., 12:4 (1967),  735–741
27. Characterization of the normal law by the property of partial sufficiency
A. M. Kagan, O. V. Shalaevskii
Teor. Veroyatnost. i Primenen., 12:3 (1967),  567–569
28. Incomplete Exponential Families and Unbiased Minimum Variance Estimates. I
A. M. Kagan, V. P. Palamodov
Teor. Veroyatnost. i Primenen., 12:1 (1967),  39–50
29. Sample mean as an estimate of the shift parameter
A. M. Kagan
Dokl. Akad. Nauk SSSR, 169:5 (1966),  1006–1008
30. The structure of a complete class of unbiased estimates for distribution families of a special form
A. M. Kagan, V. N. Sudakov
Dokl. Akad. Nauk SSSR, 164:2 (1965),  267–269
31. Questions in the theory of estimation and the testing of hypotheses
A. M. Kagan, Yu. V. Linnik
Itogi Nauki. Ser. Teor. Veroyatn. 1963, 1965,  5–48
32. Remarks on separating partitions
A. M. Kagan
Trudy Mat. Inst. Steklov., 79 (1965),  26–31
33. Sufficient systems
A. M. Kagan
Trudy Mat. Inst. Steklov., 79 (1965),  17–23
34. New classes of families of distributions allowing similar regions
A. M. Kagan
Trudy Mat. Inst. Steklov., 79 (1965),  11–16
35. The Behrens–Fisher problem for the existence of similar regions in an algebra of sufficient statistics
A. M. Kagan, O. V. Shalaevskii
Dokl. Akad. Nauk SSSR, 155:6 (1964),  1250–1252
36. Families of distributions and separating partitions
A. M. Kagan
Dokl. Akad. Nauk SSSR, 153:3 (1963),  522–525
37. On the theory of Fischer's information quantity
A. M. Kagan
Dokl. Akad. Nauk SSSR, 151:2 (1963),  277–278
38. On Robbins's scheme
A. M. Kagan
Dokl. Akad. Nauk SSSR, 150:4 (1963),  733–735
39. On an empirical Bayes approach to the problem of estimation
A. M. Kagan
Dokl. Akad. Nauk SSSR, 147:5 (1962),  1020–1021

40. Foreword of the editor
A. M. Kagan
Zap. Nauchn. Sem. LOMI, 43 (1974),  5
41. Yu. V. Linnik “Statistical problems with nuisance parameters” (book review)
A. M. Kagan
Teor. Veroyatnost. i Primenen., 13:1 (1968),  196–197

Organisations
 
Contact us:
 Terms of Use  Registration  Logotypes © Steklov Mathematical Institute RAS, 2019