TY -的A2 Muhiuddin g . AU - Aloafi Tahani a . AU - Aljohani哈桑m . PY - 2022 DA - 2022/08/13 TI -概述基于复小波系数的复合标准Elastic-Net分布SP - 9005413六世- 2022 AB -统计工具显著改变了过去十年;当最大似然方法通常应用,它提供了一个不准确的解决方案由于其不合适的属性和导致健康问题。然而,当前普通最小二乘法(OLS)模型在特定情况下更可靠的估计是基于斜率。另一方面,一些方法取决于斜率,建议和拦截。这些方法可以被描述为阈值的规则。另一个常常首选方法是后意味着(PM)技术。这个过程取决于两个部分,第一部分是可能性,,另一个是先验分布,第二部分评估中起着重要作用。在本文中,假设标准elastic-net分布的前部分,包括两个部分,第一个是正态分布和第二个双指数分布。使用这个模型的原因是,小波工具有不同级别的分辨率。因此,这个模型可以提供更准确的估计小波系数的估计可能使用一个正常或双指数分布。 In the past, some properties of elastic-net penalized were introduced and discussed. However, more properties are introduced for this distribution. In addition, two models based on the elastic-net method are demonstrated, involving the point mass prior. The first model combines normal as likelihood, and elastic-net distributions as prior, while the other combines the double exponential distribution as likelihood with the elastic-net distribution as prior. Moreover, the level-dependent components are estimated at each resolutions. A simulated investigation is studied using the Markov Chain Monte Carlo (MCMC) tool to estimate the underlying features, where real data are involved and modelled using the proposed methods. A stationary wavelet basis is also applied. As a result, the proposed procedure reduces noise levels which may be helpful since noise levels often corrupt real data, usually a significant cause of most numerical estimation problems. SN - 2314-4629 UR - https://doi.org/10.1155/2022/9005413 DO - 10.1155/2022/9005413 JF - Journal of Mathematics PB - Hindawi KW - ER -