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It is rare for the forecasts of one economic forecasting model to always be more accurate than the forecasts from an alternative model. This suggests the possibility of implementing a switching strategy that chooses, at each point in time, the forecasting model that is expected to be most accurate conditional on a set of instruments that are used to track the relative accuracy of the underlying forecasts. The authors analyze the factors determining the expected gains from such a switching rule over a strategy of always using one of the underlying forecasts. The authors derive bounds on the expected gains from switching for both the nested and non-nested cases and also analyze the case with a highly persistent (near-unit root) predictor variable.

In the modern customer‐centred era, customer value is a strategic weapon in attracting and retaining customers. Delivering superior customer value has become a matter of ongoing concern in building and sustaining competitive advantage by driving customer‐relationship‐management (CRM) performance. However, related studies are rather divergent, the key dimensions of customer value remain unclear, and there is no agreement on the evaluation of CRM performance. This paper develops an integrative framework for customer value and CRM performance based on the identification of the key dimensions of customer value. Emphasising the customer equity‐based view, the paper explores the decomposed effects of customer value on CRM performance in terms of relationship quality and customer behaviours. In doing so, a structural equation model is developed using the partial least square method supported by an empirical investigation of customers in China.

This study aims to treat a novel system of Volterra integro-differential equations with multiple delays and variable bounds, constituting a generic numerical method based on the matrix equation and a combinatoric-parametric Charlier polynomials. The proposed method utilizes these polynomials for the matrix relations at the collocation points.

Thanks to the combinatorial eligibility of the method, the functional terms can be transformed into the generic matrix relations with low dimensions, and their resulting matrix equation. The obtained solutions are tested with regard to the parametric behaviour of the polynomials with $\alpha$, taking into account the condition number of an outcome matrix of the method. Residual error estimation improves those solutions without using any external method. A calculation of the residual error bound is also fulfilled.

All computations are carried out by a special programming module. The accuracy and productivity of the method are scrutinized via numerical and graphical results. Based on the discussions, one can point out that the method is very proper to solve a system in question.

This paper introduces a generic computational numerical method containing the matrix expansions of the combinatoric Charlier polynomials, in order to treat the system of Volterra integro-differential equations with multiple delays and variable bounds. Thus, the method enables to evaluate stiff differential and integral parts of the system in question. That is, these parts generates two novel components in terms of unknown terms with both differentiated and delay arguments. A rigorous error analysis is deployed via the residual function. Four benchmark problems are solved and interpreted. Their graphical and numerical results validate accuracy and efficiency of the proposed method. In fact, a generic method is, thereby, provided into the literature.

Functionally graded materials are a special class of composites in which material are graded either continuously or layered wise depending upon its applications. With such variations of materials, the properties of structure vary either lengthwise or thickness wise. This paper aims to investigate models for effective estimation of material properties, as it is necessary for industries to identify the properties of composites or functionally graded materials (FGM’s) before manufacturing and also to develop novel material combinations.

Available models were compared for different material combinations and tested with experimental data for properties such as Young’s modulus, density, coefficient of thermal expansion (CTE) and thermal conductivity. Combinations of metal–ceramic and metal–metal were selected such that their ratios cover a wide range of materials.

This study reveals different models will be required depending on the material used and properties to be identified.

The results of the present work will help researchers in the effective modeling of composites or FGM’s for any analysis.

This paper presents a comparison and review of various analytical methods with experimental data graphically to find out the best suitable method. For the first time, the Halpin-Tsai model was extended in the analysis of the CTE which shows good approximations.

A multi-state linear k-within-(r, s)-of-(m, n): F lattice system consists of m×n components arranged in m rows and n columns. The possible states of the system and its components are: 0, 1, 2, …, H. According to k values, the system can be categorized into three special cases: decreasing, increasing and constant. The system reliability of decreasing and constant cases exists. The purpose of this paper is to evaluate the system reliability in increasing case with i.i.d components, where there is no any algorithm for evaluating the system reliability in this case.

The Boole-Bonferroni bounds were applied for evaluating the reliability of many systems. In this paper, the author reformulated the second-order Boole-Bonferroni bounds to be suitable for the evaluation of the multi-state system reliability. And the author applied these bounds for deriving the lower bound and upper bound of increasing multi-state linear k-within-(r, s)-of-(m, n): F lattice system.

An illustrated example of the proposed bounds and many numerical examples are given. The author tested these examples and concluded the cases that make the new bounds are sharper.

In this paper, the author considered an important and complex system, the multi-state linear k-within-(r, s)-of-(m, n): F lattice system; it is a model for many applications, for example, telecommunication, radar detection, oil pipeline, mobile communications, inspection procedures and series of microwave towers systems.

This paper suggests a method for the computation of the bounds of increasing multi-state linear k-within-(r,s)-of-(m,n): F lattice system. Furthermore, the author concluded that the cases that make these bounds are sharper.

When a parameter of interest is nondifferentiable in the probability, the existing theory of semiparametric efficient estimation is not applicable, as it does not have an influence function. Song (2014) recently developed a local asymptotic minimax estimation theory for a parameter that is a nondifferentiable transform of a regular parameter, where the transform is a composite map of a continuous piecewise linear map with a single kink point and a translation-scale equivariant map. The contribution of this paper is twofold. First, this paper extends the local asymptotic minimax theory to nondifferentiable transforms that are a composite map of a Lipschitz continuous map having a finite set of nondifferentiability points and a translation-scale equivariant map. Second, this paper investigates the discontinuity of the local asymptotic minimax risk in the true probability and shows that the proposed estimator remains to be optimal even when the risk is locally robustified not only over the scores at the true probability, but also over the true probability itself. However, the local robustification does not resolve the issue of discontinuity in the local asymptotic minimax risk.

Upper bound on Sharpe ratio helps to evaluate the risk-adjusted performance in real market setting. The purpose of this study is to evaluate the performance of Shariah-compliant indices (SCIs) and also estimate the upper bound on Sharpe ratio in real-market setting. For comparison, the authors also report the same statistics for conventional indices (CIs).

This study considers returns of 12 indices from Asia-Pacific and the USA for the time period May 31, 2013-Aug 25, 2022. These indices are further classified as small-, mid- and large-cap indices. The upper bound is estimated in three settings, an unconstrained setting, correlation constraint and copula constraint.

The authors found that upper bound estimation is sensitive to both the choice of index, geographic location and size of constituents within the index. Interestingly, SCIs outperform CIs both in terms of Sharpe ratio and upper bound estimations. The ability of SCIs to achieve high Sharpe ratio boosts investors’ confidence. The results are robust even after introducing correlation and copula constraints to the model.

Any violation of the upper bound on Sharpe ratio is not necessarily an indication of fraud or dubious Sharpe ratio. It should be interpreted only as a signal for inflated risk-adjusted performance and requires further investigation. Together with risk-adjusted performance, fund managers should report upper bounds to insure investor protection.

Many studies have compared the risk-adjusted performance of SCIs and CI. To the best of the authors’ knowledge, this study is the first effort to evaluate and compare the upper bounds on Sharpe ratio of SCIs in a real-market setting.

This paper aims to develop an efficient numerical method for mid-frequency analysis of built-up structures with large convex uncertainties.

Based on the Chebyshev polynomial approximation technique, a Chebyshev convex method (CCM) combined with the hybrid finite element/statistical energy analysis (FE-SEA) framework is proposed to fulfil the purpose. In CCM, the Chebyshev polynomials for approximating the response functions of built-up structures are constructed over the uncertain domain by using the marginal intervals of convex parameters; the bounds of the response functions are calculated by applying the convex Monte–Carlo simulation to the approximate functions. A relative improvement method is introduced to evaluate the truncated order of CCM.

CCM has an advantage in accuracy over CPM when the considered order is the same. Furthermore, it is readily to consider the CCM with the higher order terms of the Chebyshev polynomials for handling the larger convex parametric uncertainty, and the truncated order can be effectively evaluated by the relative improvement method.

The proposed CCM combined with FE-SEA is the first endeavor to efficiently handling large convex uncertainty in mid-frequency vibro-acoustic analysis of built-up structures. It also has the potential to serve as a powerful tool for other kinds of system analysis when large convex uncertainty is involved.

We show how to use a smoothed empirical likelihood approach to conduct efficient semiparametric inference in models characterized as conditional moment equalities when data are collected by variable probability sampling. Results from a simulation experiment suggest that the smoothed empirical likelihood based estimator can estimate the model parameters very well in small to moderately sized stratified samples.

L. Gǎvruţa (2012) introduced a special kind of frames, named K-frames, where K is an operator, in Hilbert spaces, which is significant in frame theory and has many applications. In this paper, first of all, we have introduced the notion of approximative K-atomic decomposition in Banach spaces. We gave two characterizations regarding the existence of approximative K-atomic decompositions in Banach spaces. Also some results on the existence of approximative K-atomic decompositions are obtained. We discuss several methods to construct approximative K-atomic decomposition for Banach Spaces. Further, approximative _d-frame and approximative _d-Bessel sequence are introduced and studied. Two necessary conditions are given under which an approximative _d-Bessel sequence and approximative _d-frame give rise to a bounded operator with respect to which there is an approximative K-atomic decomposition. Example and counter example are provided to support our concept. Finally, a possible application is given.