Linearity of regression for non-adjacent weak records

Statistica Sinica

Volumn 11, Issue 1, 2001, Pages 39-52

  Wesołowski, Jacek ^a   Ahsanullah, Mohammad ^b  

^a WARSAW UNIVERSITY OF TECHNOLOGY   (Poland)

^b RIDER UNIVERSITY   (United States)

Author keywords

Beta negative binomial distribution; Difference equations; Geometric distribution; Linearity of regression; Negative hypergeometric distribution; Weak records

Indexed keywords

EID: 0345775316     PISSN: 10170405     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (27)

1. Ahsanullah, M. (1995). Record Statistics. Nova Science Publishers, Commack, New Jersey.
2. Ahsanullah, M. and Holland, B. (1984). Record values and the geometric distribution. Statist. Hefte 25, 319-327.
3. Aliev, F. A. (1998). Characterizations of distributions through weak records. J. Appl. Statist. Sci. 8, 13-16.
4. Arnold, B. C., Balakrishnan, N. and Nagaraja, H. N. (1992). A First Course in Order Statistics. Wiley, New York.
5. Arnold, B. C., Balakrishnan, N. and Nagaraja, H. N. (1998). Records. Wiley, New York.
6. Asadi, M., Rao, C. R. and Shanbhag, D. N. (1999). Some unified characterization results on generalized Pareto distributions. Preprint, 1-23.
7. Balakrishnan, N. and Balasubramanian, K. (1995). A characterization of geometric distribution based on records. J. Appl. Statist. Sci. 2, 277-282.
8. Deheuvels, P. (1984). The characterization of distributions by order statistics and record values - a unified approach. J. Appl. Probab. 21, 326-334. (Correction. Ibidem 22, 997.)
9. Dembińska, A. and Wesołowski, J. (1998). Linearity of regression for non-adjacent order statistics. Metrika 48, 215-222 .
10. Dembińska, A. and Wesołowski, J. (2000). Linearity of regression for non-adjacent records. J. Statist. Plann. Inference. To appear.
11. Ferguson, T. S. (1967). On characterizing distributions by properties of order statistics. Sankhyā Ser. A 29, 265-278.
12. Huang, W.-J. and Li, S.-H. (1993). Characterization results based on record values. Statist. Sinica 3, 583-599.
13. Huang, W.-J. and Su, J.-S. (1999). On certain problems involving order statistics - a unified approach through order statistics property of point processes. Sankhā Ser. A 61, 36-49.
14. Johnson, N. L., Kotz, S. and Kemp, A. (1992). Discrete Univariate Distributions. Wiley, New York.
15. Kamps, U. (1995). A Concept of Generalized Order Statistics. B.G. Teubner, Stuttgart.
16. Kirmani, S. N. U. A. and Alam, S. N. (1980). Characterization of the geometric distribution by the form of a predictor. Comm. Statist. Theory Methods 9, 541-547.
17. Korwar, R. M. (1984). On characterizing distributions for which the second record value has a linear regression on the first. Sankhyā Ser. B 46, 108-109.
18. López-Blázquez, F. and Salamanca-Miño, B. (1998). A characterization of the geometric distribution. Statist. Papers 39, 231-236.
19. Nagaraja, H. N. (1977). On a characterization based on record values. Austral. J. Statist. 19, 70-73.
20. Nagaraja, H. N. (1988). Some characterizations of discrete distributions based on linear regressions of adjacent order statistics. J. Statist. Plann. Inference 20, 65-75.
21. Nagaraja, H. N. (1992). Order statistics from discrete distributions. Statist. 23, 189-216.
22. Nagaraja, H. N., Sen, P. and Srivastava, R. C. (1989). Some characterizations of geometric tail distributions based on record values. Statist. Papers 30, 147-155.
23. Rao, C. R. and Shanbhag, D. N. (1986). Recent results on characterization of probability distributions: a unified approach through extensions of Deny's theorem. Adv. Appl. Probab. 18, 660-678.
24. Srivastava, R. C. (1979). Two characterizations of the geometric distribution by record values. Sankhyā Ser. B 40, 276-278.
25. Stepanov, A. V. (1990). Characterizations of a geometric class of distributions. Theory Probab. Math. Statist. 41, 133-136.
26. Stepanov, A. V. (1994). A characterization theorem for weak records. Theory Probab. Appl. 38, 762-764.
27. Vervaat, W. (1973). Limit theorems for records from discrete distributions. Stochastic Process. Appl. 1, 317-334.