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Abstract: This paper applied the maximization by parts (MBP) and the modified MBP (MMBP) methods to estimate the C-MGARCH model and compare the effectiveness of two methods. Monte Carlo simulation studies show that both MBP and MMBP methods are more efficient than that of the IFM method. [Copyright &y& Elsevier]

Abstract: Any repairable system improves (deteriorates) with time if the interarrival times of failure tend to get larger (smaller) in some sense. In this paper we consider two such repairable systems, and their performance in terms of several partial orderings of their respective interarrival times of failure are compared. The comparison of two systems’ improvement/deterioration under minimal repair policy has been characterized in terms of - orders and also in terms of their shifted and dispersive versions. These results generalize some of the existing results in the literature and also provide some new results in this direction. [ABSTRACT FROM AUTHOR]

Abstract: In this paper I return to the issue of estimating linear state space models with constrained state vectors. My endeavor is towards the following tasks: (i) to give a new elementary derivation for restricted Kalman filtering under augmentation of the measurement equation, (ii) to prove the statistical efficiency due to the imposition of restrictions using a geometrical framework, and (iii) to propose an alternative approach for imposing time-invariant restrictions to the estimation of random walk state vectors. [Copyright &y& Elsevier]

Abstract: In this note we show that the locally stationary wavelet process can be decomposed into a sum of signals, each of which follows a moving average process with time-varying parameters. We then show that such moving average processes are equivalent to state space models with stochastic design components. Using a simple simulation step, we propose a heuristic method of estimating the above state space models and then we apply the methodology to foreign exchange rates data. [Copyright &y& Elsevier]

Abstract: Let be gap times corresponding to two consecutive events, which are observed subject to random right-censoring. In this paper a simple estimator of the bivariate distribution function of is proposed. We investigate the conditions under which the introduced estimator is consistent. Applications to the estimation of the marginal distributions of the gap times and to correlation analysis are included. We explore the behaviour of the proposed methods through simulations. [Copyright &y& Elsevier]

Abstract: In this paper, an empirical Bayes (EB) estimator is derived for the estimable functions of the parameters in normal linear model. The superiority of the EB estimator over ordinary least-squares (LS) estimator is investigated under mean square error matrix (MSEM) criterion. [Copyright &y& Elsevier]

Abstract: An alternative criterion is presented for a linear function of the unknown parameters, in a linear model, to be estimable. If there is a linear relationship between members of a subset of the columns of the design matrix , then the parameters associated with all the columns in that subset are not estimable. Also any part of their linear relationship is non-estimable. [Copyright &y& Elsevier]

Abstract: In [Przystalski M., Krajewski P., 2007. Constrained estimators of treatment parameters in semiparametric models. Statist. Probab. Lett. 77, 914–919] we presented a method of estimation of treatment effects in a semiparametric model with one smoothing term under additional conditions on their linear functions and its application to hypothesis testing. In this note we will present the corrected version of the proof of Theorem 3.1. [Copyright &y& Elsevier]