MATVines: A vine copula package for MATLAB

Coblenz, Maximilian

doi:10.1016/j.softx.2021.100700

Cited by 21 publications

(8 citation statements)

References 19 publications

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“…Besides, the copula-based PDF are also obtained using Cayton copula and Gumbel copula. 36 It is observed that the proposed method can provide the most accurate approximation to the PDF of the simulated RUL.…”

Section: Rul Predictionmentioning

confidence: 90%

“…For comparison purposes, our proposed approximated PDF of the RUL is also plotted in Figure 13 based on the method in Section 3.3. Besides, the copula‐based PDF are also obtained using Cayton copula and Gumbel copula 36 . It is observed that the proposed method can provide the most accurate approximation to the PDF of the simulated RUL.…”

Section: Actual Applicationmentioning

confidence: 99%

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Correlation‐driven multivariate degradation modeling and RUL prediction based on Wiener process model

Yan

Wang

2022

Quality & Reliability Eng

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For degraded products with multiple performance characteristics (PCs), one way to model their degradation process is by using a multivariate independent Wiener process model with random drift. However, it fails to capture the latent correlation in degradation paths for multiple PCs caused by the common environmental condition. In this paper, we model the degradation processes of multiple PCs using multiple correlated Wiener processes. The commonly shared environmental condition function incorporates the degradation correlation and random effect. Thus, it directly catches the strong correlation of degradation rates and volatilities to all dimensions of multiple PCs. Our model is more economical in the number of parameters than the multivariate independent Wiener process. The correlation coefficients and RUL distribution approximation are provided in closed forms. We extend the proposed model to a two‐stage degradation process to correlate multiple PCs in each stage. An adaptive drift is adopted in the Wiener process model for the real‐time degradation states updating with the help of the Bayesian and the expectation‐maximization (EM) algorithm. The proposed model's effectiveness is illustrated by numerical studies and a real‐world application to the wheel treads on high‐speed trains.

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Section: Rul Predictionmentioning

confidence: 90%

Section: Actual Applicationmentioning

confidence: 99%

Correlation‐driven multivariate degradation modeling and RUL prediction based on Wiener process model

Yan

Wang

2022

Quality & Reliability Eng

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“…The matrix representation was introduced to show that the number of regular vines on d nodes is 27 . The matrix representation is used in software implementations in R 30 , P ython 32 and matlab 31 . Our data consists precisely of all 24 4 × 4 matrices representing regular vines on 4 nodes, 480 5 × 5 matrices representing regular vines on 5 nodes, 24,030 6 × 6 matrices representing regular vines on 6 nodes, 2,580,480 7 × 7 matrices representing regular vines on 7 nodes and 660,602,880 8 × 8 matrices representing regular vines on 8 nodes.…”

Section: Methodsmentioning

confidence: 99%

Chimera: An atlas of regular vines on up to 8 nodes

et al. 2023

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Vine copulas have become the standard tool for modelling complex probabilistic dependence. It has been shown that the number of regular vines grows extremely quickly with the number of nodes. Chimera is the first attempt to map the vast space of regular vines. Software for operating with regular vines is available for R, matlab and Python. However, no dataset containing all regular vines is available. Our atlas of regular vines, Chimera, comprises all 24 4 × 4 matrices representing regular vines on 4 nodes, 480 5 × 5 matrices representing regular vines on 5 nodes, 23,040 6 × 6 matrices representing regular vines on 6 nodes, 2,580,480 7 × 7 matrices representing regular vines on 7 nodes and 660,602,880 8 × 8 matrices representing regular vines on 8 nodes. Regular vines in Chimera are classified according to their tree-equivalence class. We fit all regular vines to synthetic data to demonstrate the potential of Chimera. Chimera provides thus a tool for researchers to navigate this vast space in an orderly fashion.

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“…Matlab digunakan karena aplikasi ini didukung dengan perangkat lunak matematika, grafis, dan kemampuan pemrograman . Aplikasi ini memiliki fungsi bawaan untuk melakukan banyak operasi [24][25] [26].…”

Section: Pendahuluanunclassified

Penerapan Metode Median Filtering untuk Optimasi Deteksi Wajah pada Foto Digital

Sunardi

Yudhana

Wijaya

2022

jinita

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Face detection in digital photos aims to get the face area in the photo. Problems often occur when detecting faces, namely there is a lot of noise in digital photos so that it affects the detection process. Therefore, in this study apply the median filtering method to improve digital photos by reducing noise in the photos to be tested. The advantage of using this filter is to keep the edges smooth while reducing noise which aims to improve image quality. The ability of this method is measured using the parameters of Mean Square Error (MSE) and Peak Noise to Signal Ratio (PNSR). When the MSE value obtained is low and the PNSR value obtained is high, the results can be said to be good. The method used to detect faces in this research, viola-jones, was chosen because it is one of the face detection procedures with a high level of accuracy and good computational ability. The sample used in this study consisted of 10 digital photos taken using a Samsung A11 smartphone camera with a resolution of 13 mega pixels and 8 mega pixels in JPEG format. The results obtained in this study are the best error values in MSE 0.9517 and PSNR 24.2804. Based on these results, it can be concluded that the mean filtering method is feasible to be used in the case of face detection in this digital photo

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MATVines: A vine copula package for MATLAB

Cited by 21 publications

References 19 publications

Correlation‐driven multivariate degradation modeling and RUL prediction based on Wiener process model

Correlation‐driven multivariate degradation modeling and RUL prediction based on Wiener process model

Chimera: An atlas of regular vines on up to 8 nodes

Penerapan Metode Median Filtering untuk Optimasi Deteksi Wajah pada Foto Digital

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