Abstract
In this paper, we study the number of near minimum-concomitant observations for Progressively Type-II Censored Order Statistics (PCOS). We first define the concomitants of PCOS and the number of near minimum-concomitant observations. We then investigate distributional and asymptotic properties of these random variables. Finally, we propose simulation techniques for generating the concomitants of PCOS.
Similar content being viewed by others
References
Aggarwala R, Balakrishnan N (1997) Some properties of progressive censored order statistics from arbitrary and uniform distributions with applications to inference and simulation. J Stat Plan Inference 70:35–49
Bairamov I (2006) Progressive type II censored order statistics for multivariate observations. J Multivar Anal 97:797–809
Bairamov I, Eryilmaz S (2005) Spacings, exceedances and concomitants in progressive type II censoring scheme. J Stat Plan Inference 136:527–536
Bairamov I, Stepanov A (2010) Numbers of near-maxima for the bivariate case. Stat Probab Lett 80:196–205
Bairamov I, Stepanov A (2011) Numbers of near bivariate record-concomitant observations. J Multivar Anal 102:908–917
Bhattacharyya BB (1974) Convergence of sample paths of normalized sums of induced order statistics. Ann Stat 2:1034–1039
Balakrishnan N, Cohen AC (1991) Order statistics and inference: estimation methods. Academic Press, San Diego
Balakrishnan N, Sandhu RA (1995) A simple simulation algorithm for generating progressive type -II censored samples. Am Stat 49:229–230
Balakrishnan N, Sandhu RA (1996) Best linear unbiased and maximum likelihood estimation for exponential distributions under general progressive type II censored samples. Sankhya Ser. B 58:1–9
Balakrishnan N, Cramer E, Kamps U (2001a) Bounds for means and variances of progressive type II censored order statistics. Stat Probab Lett 54:301–315
Balakrishnan N, Cramer E, Kamps U, Schenk N (2001b) Progressive type II censored order statistics from exponential distributions. Statistics 35:537–556
Balakrishnan N, Kim JA (2005) EM Algorithm and optimal censoring schemes for progressively type-II censored bivariate normal data. In: Book advances in ranking and selection, multiple comparisons, and reliability statistics for industry and technology, pp 21–45
Balakrishnan N, Stepanov A (2008) Asymptotic properties of numbers of near minimum observations under progressive type-II censoring. J Stat Plan Inference 38:1010–1020
Balasooriya U, Balakrishnan N (2000) Reliability sampling plans for lognormal distribution, based on progressively censored samples. IEEE Trans Reliab 49:199–203
Cohen AC (1991) Truncated and censored samples theory and applications. Marcel Dekker, New York
Cohen AC, Whitten BJ (1988) Parametric inference for life span and reliability models. Marcel Dekker, New York
David HA (1973) Concomitants of order statistics. Bull Inst Internat Stat 45:295–300
Kamps U, Cramer E (2001) On distributions of generalized order statistics. Statistics 35:269–281
Lawless JF (1982) Statistical models and methods for lifetime data. Wiley, New York
Nelson W (1982) Applied life data analysis. Wiley, New York
Ng HKT, Chan PS, Balakrishnan N (2004) Optimal progressive censoring plans for the Weibull distribution. Technometrics 46:470–481
Viveros R, Balakrishnan N (1994) Interval estimation of life parameters based on progressively censored data. Technometrics 36:84–91
Acknowledgments
The second author’s work is done within the scienticfic task N 2014/60/2077 “Mathematical Theory of Extreme Values” financed from the federal budget by the ministry of education of Russian Federation.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Berred, A., Stepanov, A. Asymptotic properties of the number of near minimum-concomitant observations in the case of progressive type-II censoring. Metrika 78, 283–294 (2015). https://doi.org/10.1007/s00184-014-0502-z
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00184-014-0502-z
Keywords
- Progressive type-II censoring
- Order statistics
- Concomitants of order statistics
- Near minimum-concomitants