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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...
The main goal of this paper is to model variance and volatility swap using superposition of Barndorff-Nielsen and Shephard (BN-S) type models. In particular, in this paper we propose superposition of Lévy process driven by Γ(ν,α) and Inverse Gaussian distributions. Model performance is assessed on data not used to build the model (i.e., test data). It is shown that the prediction error rate for the...
Intrinsic dimensionality estimation plays a pivotal role in dealing with high-dimensional datasets. In this work, we aim to develop a robust dimensionality estimation algorithm by investigating the intrinsic dimensionality estimation methods for data points in its local region. Our method is able to effectively utilise the geometric information in the local region for dimensionality. We also show...
When linear, binary or count responses are collected from a series of (spatial) locations, the responses from adjacent/neighboring locations are likely to be correlated. To model the correlation between the responses from two adjacent locations, many existing studies assume that the two locations belong to a family and their responses are correlated through the random effects of common locations shared...
The analysis of progressively censored data has received considerable attention in the last few years. In this paper, we consider the joint progressive censoring scheme for two populations. It is assumed that the lifetime distribution of the items from the two populations follows Weibull distribution with the same shape but different scale parameters. Based on the joint progressive censoring scheme,...
In this paper we construct ‘inter-class orthogonal’ main effect plans (MEPs) for asymmetrical experiments. In such a plan, the factors are partitioned into classes so that any two factors from different classes are orthogonal. We have also defined the concept of “partial orthogonality” between a pair of factors. In many of our plans, partial orthogonality has been achieved when (total) orthogonality...
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