In this study, we modeled the multi-model blending process using random variables and explicitly derived the distribution of the blended forecast error under the assumption of normally distributed errors. Utilizing th...
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In this study, we modeled the multi-model blending process using random variables and explicitly derived the distribution of the blended forecast error under the assumption of normally distributed errors. Utilizing this error distribution, we regained the scalar version of the Best Linear Unbiased Estimator. Notably, the model yielded negative weights, which contradict traditional assumptions that weights should be positive. To address this, we modified the algorithm to set negative weights to zero and compared the performance with the original algorithm. Our findings indicate that setting negative weights to zero results in a slight improvement in blending performance compared to using negative weights directly. This improvement may be attributed to modeling the actual forecast error as a normally distributed unified parameter and applying a consistent correlation coefficient across the annual data set.
Buffeting displacements bridge girders commonly bridge design's comfort, operational, and strength limit states. The scattered nature of the main wind characteristics and bridge responses recorded in multiple moni...
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Buffeting displacements bridge girders commonly bridge design's comfort, operational, and strength limit states. The scattered nature of the main wind characteristics and bridge responses recorded in multiple monitoring campaigns make deterministic approaches insufficient to assess the bridge's performance along its life span. This study reports comprehensive sensitivity and reliability studies conducted to unveil the influence of multiple parameters controlling long-span bridges' buffeting responses. impact of several sets of random variables on the reliability of the Great Belt Bridge is systematically studied. A detailed treatment of the uncertainty of flutter derivatives consisting of combining their frequency-dependent random definition with their experimentally defined correlation is proposed. Results show the drastic impact of uncertainty in the flutter derivatives, the vertical turbulence intensity, the mean wind velocity, the definition of the buffeting loads, particularly the slopes of the force coefficients and the aerodynamic admittance, on the buffeting-induced accelerations. The influence of aerodynamic admittance on the results is analyzed in the context of random definitions of mean velocity, turbulent intensities, length scales, structural damping, and aerodynamic characteristics. The computational efficiency of gradient-based reliability methods discussed, showing its potential to address high-dimensional problems within design frameworks.
The divergence information measures play a significant role in quantifying the discrimination between two probability distributions. Two conventional divergence measures, the Kullback-Leibler divergence and the Pearso...
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The divergence information measures play a significant role in quantifying the discrimination between two probability distributions. Two conventional divergence measures, the Kullback-Leibler divergence and the Pearson chi(2) -divergence, possess significant importance in information theory, signal processing, data science and other associated fields. In this manuscript, the Pearson chi(2) -divergence measure between two doubly truncated non-negative random variables is proposed. The proposed measure quantifies the amount of information lost inside a truncated interval when an assumed or estimated distribution is used instead of the actual distribution. It is shown that Pearson's chi(2) -divergence measure characterizes the distribution uniquely under certain conditions. Several upper and lower bounds have been derived. The implications of monotonic transformations on the proposed measure are thoroughly examined. Further, the doubly truncated chi(2) -divergence for exponential populations has been estimated by a simulation study. In addition, we demonstrated the application using real world data to illustrate the utility of the new measure. Finally, we concluded our findings with possible future scopes.
The fluctuating two-ray (FTR) fading model has proven to effectively characterize small-scale fading in gigahertz and terahertz frequency bands. In these wireless scenarios, one can enhance the system performance by e...
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The fluctuating two-ray (FTR) fading model has proven to effectively characterize small-scale fading in gigahertz and terahertz frequency bands. In these wireless scenarios, one can enhance the system performance by exploiting multiple communication links, where sums of random variables (RVs) commonly arise and, therefore, need to be statistically addressed to evaluate the system behavior. Unfortunately, the statistical analysis of such sums is rather challenging, which has motivated further research to find exact solutions. In this article, we characterize the exact statistics of sums of independent and identically distributed squared FTR RVs. Specifically, we derive novel improved expressions for the probability density function (PDF) and the cumulative distribution function (CDF). Our expressions demonstrated to be lighter, faster, and more manageable than the state-of-the-art solutions. More importantly, we show that the sum PDF and the sum CDF can be written as a random mixture of not necessarily identically distributed gamma PDFs and CDFs, respectively. Capitalizing on our findings, we assess the performance of multi-branch maximal-ratio combining receivers operating over FTR fading channels, considering three essential metrics: average bit-error rate, outage probability, and ergodic capacity. Simulation results confirm the validity and efficiency of our analytical derivations.
The authors study the strong limit theorems for pairwise negatively quadrant dependent random variables, and present a new Jajte-type theorem on the complete convergence and the strong laws of large numbers. The resul...
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We obtain asymptotic approximations for the probability density function of the product of two correlated normal random variables with non-zero means and arbitrary variances. As a consequence, we deduce asymptotic app...
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We obtain asymptotic approximations for the probability density function of the product of two correlated normal random variables with non-zero means and arbitrary variances. As a consequence, we deduce asymptotic approximations for the tail probabilities and quantile functions of this distribution, as well as an asymptotic approximation for the widely used risk measures value at risk and tail value at risk. (c) 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons .org /licenses /by /4 .0/).
作者：
Gao, QiMiao, YuHenan Normal Univ
Coll Math & Informat Sci Xinxiang 453007 Henan Peoples R China Henan Normal Univ
Henan Engn Lab Big Data Stat Anal & Optimal Contro Xinxiang 453007 Henan Peoples R China
In the present paper, we consider a sequence of the general random variables, which include the sequences of martingale differences, and establish the weak law of large numbers and the convergence in L-p under some we...
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In the present paper, we consider a sequence of the general random variables, which include the sequences of martingale differences, and establish the weak law of large numbers and the convergence in L-p under some weaker conditions.
In this work, by using Marcinkiewicz-Zygmund type moment inequality of asymptotically negatively associated (ANA, in short) sequences, the strong law of large numbers of linear processes with random coefficients gener...
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Simulation has become a modern-day tool that helps us study many systems that its results could not have been studied or predicted through the work of these systems over time. The simulation process depends on generat...
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Analysis using simulation is a natural and logical extension of the analytical and mathematical models inherent in operations research. Simulation has become a modern tool that helps in studying many systems that we c...
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