Sankhya, the Indian Journal of Statistics is the official publication of the Indian Statistical Institute. This quarterly journal publishes research articles in the broad areas of Theoretical Statistics, Applied Statistics, Mathematical Statistics and Probability. Each year the Journal is published in two Series. Series A, published in February and August, primarily covers Mathematical Statistics and Probability. Series B, published in May and November, primarily covers Applied and Interdisciplinary Statistics. In case of overlapping topics, the applied and theoretical flavors of the paper are considered to determine the appropriate series.
Sankhya B
Description
Identifiers
ISSN | 0976-8386 |
e-ISSN | 0976-8394 |
DOI | 10.1007/13571.0976-8394 |
Publisher
Springer India
Additional information
Data set: Springer
Articles
Re-parametrization is often done to make a constrained optimization problem an unconstrained one. This paper focuses on the non-parametric maximum likelihood estimation of the sub-distribution functions for current status data with competing risks. Our main aim is to propose a method using re-parametrization, which is simpler and easier to handle with compared to the constrained maximization methods...
The family of Inverse Gaussian (IG) distributions has applications in areas such as hydrology, lifetime testing, and reliability, among others. In this paper, a new characterization for this family of distributions is introduced and is used to propose a test of fit for the IG distribution hypothesis with unknown parameters. As a second test, observations are transformed to normal variables and then...
Kullback-Leibler divergence ( K ℒ ) $(\mathcal {K}\mathcal {L})$ is widely used for selecting the best model from a given set of candidate parametrized probabilistic models as an approximation to the true density function h(·). In this paper, we obtain a necessary and sufficient condition to determine proportional hazard and reversed hazard rate models based on symmetric and asymmetric Kullback-Leibler...