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A Unit Root Test for an AR(1)Process with AR Errors by Using Random Weighted Bootstrap
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作者 Xiao Hui Liu Ya Wen Fan +1 位作者 Yu Zi Liu Shi Hua Luo 《Acta Mathematica Sinica,English Series》 SCIE CSCD 2023年第9期1834-1854,共21页
A great deal of economic problems are related to detecting the stability of time series data,where the main interest is in the unit root test.In this paper,we consider the unit root testing problem with errors being l... A great deal of economic problems are related to detecting the stability of time series data,where the main interest is in the unit root test.In this paper,we consider the unit root testing problem with errors being long-memory processes with the LARCH structure.A new test statistic is developed by using the random weighted bootstrap method.It turns out that the proposed statistic has a chisquared distribution asymptotically regardless of the process being stationary or nonst at ionary,and with or without an intercept term.The simulation results show that the statistic has a desired finite sample performance in terms of both size and power.A real data application is also given relying on the inflation rate data of 17 countries. 展开更多
关键词 Autoregressive model random weighted bootstrap autoregressive errors unit root test
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Multivariate Aggregated NOMA for Resource Aware Wireless Network Communication Security
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作者 V.Sridhar K.V.Ranga Rao +4 位作者 Saddam Hussain Syed Sajid Ullah Roobaea Alroobaea Maha Abdelhaq Raed Alsaqour 《Computers, Materials & Continua》 SCIE EI 2023年第1期1693-1708,共16页
NonorthogonalMultiple Access(NOMA)is incorporated into the wireless network systems to achieve better connectivity,spectral and energy effectiveness,higher data transfer rate,and also obtain the high quality of servic... NonorthogonalMultiple Access(NOMA)is incorporated into the wireless network systems to achieve better connectivity,spectral and energy effectiveness,higher data transfer rate,and also obtain the high quality of services(QoS).In order to improve throughput and minimum latency,aMultivariate Renkonen Regressive Weighted Preference Bootstrap Aggregation based Nonorthogonal Multiple Access(MRRWPBA-NOMA)technique is introduced for network communication.In the downlink transmission,each mobile device’s resources and their characteristics like energy,bandwidth,and trust are measured.Followed by,the Weighted Preference Bootstrap Aggregation is applied to recognize the resource-efficient mobile devices for aware data transmission by constructing the different weak hypotheses i.e.,Multivariate Renkonen Regression functions.Based on the classification,resource and trust-aware devices are selected for transmission.Simulation of the proposed MRRWPBA-NOMA technique and existing methods are carried out with different metrics such as data delivery ratio,throughput,latency,packet loss rate,and energy efficiency,signaling overhead.The simulation results assessment indicates that the proposed MRRWPBA-NOMA outperforms well than the conventional methods. 展开更多
关键词 Mobile network multivariate renkonen regression weighted preference bootstrap aggregation resource-aware secure data communication NOMA
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