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Initialization plays an important role in the accuracy of endmember extraction algorithms (EEAs) in linear hyperspectral unmixing (LHU). Random initialization can lead to varying endmembers generated by EEAs. To address this challenge, an initialization strategy has been introduced, encompassing vertex component analysis (VCA), automatic target generation process (ATGP), among others. These techniques significantly contribute to enhancing the accuracy of EEAs. However, complex initialization is sometimes less preferable, prompting the unexplored question of whether there exists an EEA robust to initialization. This paper focuses on analyzing this issue within the context of minimum simplex volume-based (MV) methods, which have received considerable attention in the past two decades due to their robustness against the absence of pure pixels. MV methods typically formulate LHU as an optimization problem, most of which includes a non-convex volume term. Additionally, many MV methods use VCA as an initialization strategy. Firstly, this paper demonstrates that the variable splitting augmented Lagrangian approach (SISAL), as a representative non-convex MV method, heavily depends on initialization. To our knowledge, the impact of initialization for MV methods has not been thoroughly analyzed before. Furthermore, this paper proposes an initially robust MV method by introducing a new convex MV term. Numerical experiments conducted on simulated and real datasets demonstrate its outstanding performance in accuracy and robustness to initialization. Throughout the experiments the proposed method proves to be the most stable, which is crucial in real scene where the ground truth is unknown beforehand. [ABSTRACT FROM AUTHOR]

AbstractThis paper proposes two new estimation methods to fit a multiple structural measurement error model when all variables are subject to errors. The new estimation methods were extensions of the Wald estimation method, one is the weighted grouping method, and the other is the iterative method. A Monte Carlo experiment is performed to investigate the performance of the new estimators compared with the classical estimation methods; the Maximum Likelihood Estimator and Method of Moment, in terms of root mean square error and its bias. The simulation outcomes demonstrated that the suggested estimators are more effective than conventional estimators. In addition, real data analysis is discussed to examine the relationship between the national gross domestic product, unemployment rate, and human development index after applying the two proposed estimation methods. [ABSTRACT FROM AUTHOR]

The asymptotic properties of nonparametric kernel estimators of diffusion process and integrated diffusion process were studied by scholars through using the theories of local time, giving the properties of consistency and asymptotic normality for nonparametric kernel estimators under appropriate conditions, but not property of strong consistency for integrated diffusion process. Instead of using the local time method, the paper applies the moment inequality of the ρ-mixing sequence to prove the strong consistency of the nonparametric kernel estimators in the integrated diffusion process. Our theorem conditions are mild and canonical, and some of them improve on the existing corresponding conditions. In numerical simulations and analysis of data from real applications, the nonparametric kernel estimators can capture well the variation characteristics of drift coefficient and diffusion coefficient, and that it is possible to fit parametric models with such characteristics, so that the economic interpretation of the models can be obtained. [ABSTRACT FROM AUTHOR]

In contrast to much of the extant literature, the paper devises a composite security burden measure for the NATO alliance that accounts for three different contributions by allies to their collective security: namely, military expenditure (ME), foreign assistance, and UN peacekeeping spending. Generally, NATO defense burden sharing and free riding are judged solely based on ME even though foreign assistance and peacekeeping promote world prosperity, stabilize regimes, and quell conflicts that affect NATO's collective security. Our parametric tests for free riding apply a spatial-lag panel model, which addresses the interdependency issues, to a broader security-spending measure that accounts for allies' membership, contiguity, and inverse distance. In all spatial models, we uncover robust evidence of free riding where allies decrease their aggregate security spending in response to increases in the collective security spending of other allies. We apply a panel generalized method of moments (GMM) estimator to adjust for endogeneity concerns. [ABSTRACT FROM AUTHOR]

This paper seeks to contribute to the burgeoning research on corporate governance and research and development (R&D) by exploring the contingent role of firm size and its crucial role in defining conditions for competitive advantage. Using a generalised method of moments (GMM) estimator and a sample of U.S. publicly traded pharmaceutical firms from 2009 to 2018, we test several hypotheses related to the role of firm size in the relationship between corporate governance and R&D investment. Our findings show the importance of institutional context and point out the configurations of governance practices that lead to high and low levels of R&D investment. We find that the effect of corporate governance on R&D investment is contingent upon firm size. Larger and smaller firms differ in building and employing their strategic decisions. Our results indicate that larger firms facilitate R&D investment than smaller firms, showing that these firms are more prone to seek variation and visibility for accessing better resources. Our findings are relevant for firms aiming to implement strong governance mechanisms to track their R&D activities and for policymakers interested in promoting R&D investment. [ABSTRACT FROM AUTHOR]

In this paper, we examine how foreign direct investment inflows in agriculture affect the agricultural exports of developing countries. The main objective of our analysis is to identify and quantify the export effects of foreign direct investment in the sector, as well as the effects of other relevant export determinants, and to explore the possible long-run relationship between the variables. Using panel data on 80 developing countries observed in the period 2005-2017, we employ the system-generalised method of moments and the method of quasi-maximum likelihood to estimate a dynamic agricultural exports model. Additionally, we test for the cointegration between exports and foreign direct investment using the Pedroni and Kao approaches. We find that foreign direct investment inflows have a positive impact on agricultural exports in the analysed countries in both the short run and the long run. Thereby, we identified the significance of both direct and spillover export effects. This implies that the liberalisation and promotion of foreign investment in agriculture could alleviate the problems of capital scarcity and constraints in developing countries and increase their agricultural export competitiveness. [ABSTRACT FROM AUTHOR]

This paper proposes a stochastic method to solve the weak correlation of lateral-vertical forces when the train crosses a bridge. This method treats the Kalker creep equation with Taylor series and uses the moment statistical method to approximate the numerical characteristics of the nonlinear terms of the equation. The variance recursive method, mean recursive method, and lateral linear creep force modulation function are proposed. Based on these methods, the approximate numerical solutions for the standard deviation of the lateral linear creep force and the correlation coefficient of the lateral-vertical forces are obtained and verified by Monte Carlo method (MCM). Under certain preconditions, the derailment factor considering the correlation of the wheel-rail forces obeys the Approximate Cauchy Distribution, which is verified by the Kolmogorov–Smirnov test. The correctness of the proposed method is validated comparing the similarity of the derailment factor extreme value cumulative distribution function curve obtained by MCM. The case of a 6-car Pioneer EMU running through a 3-span 32 m simply-supported bridge is concerned by the proposed method and it is found that there is a significant difference with different traffic intense of the railway. [ABSTRACT FROM AUTHOR]