應(yīng)yl7703永利官網(wǎng)李周平教授邀請(qǐng)，西南財(cái)經(jīng)大學(xué)常晉源教授將于2023年3月7日上午進(jìn)行線上學(xué)術(shù)報(bào)告，歡迎全校師生參加。

報(bào)告題目：On the Modelling and Prediction of High-Dimensional Functional Time Series

時(shí) 間：3月7日（星期二）上午10:00

地 點(diǎn)：騰訊會(huì)議（會(huì)議 ID：727-181-958）

報(bào)告摘要：We propose a two-step procedure to model and predict high-dimensional functional time series, where the number of function-valued time series $p$ is large in relation to the length of time series $n$. Our first step performs an eigenanalysis of a positive definite matrix, which leads to a one-to-one linear transformation for the original high-dimensional functional time series, and the transformed curve series can be segmented into several groups such that any two subseries from any two different groups are uncorrelated both contemporaneously and serially. Consequently in our second step those groups are handled separately without the information loss on the overall linear dynamic structure. The second step is devoted to establishing a finite-dimensional dynamical structure for all the transformed functional time series within each group. Furthermore the finite-dimensional structure is represented by that of a vector time series. Modelling and forecasting for the original high-dimensional functional time series are realized via those for the vector time series in all the groups. We investigate the theoretical properties of our proposed methods, and illustrate the finite-sample performance through both extensive simulation and three real datasets.

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常晉源教授簡(jiǎn)介

常晉源，西南財(cái)經(jīng)大學(xué)光華特聘教授、博士生導(dǎo)師、數(shù)據(jù)科學(xué)與商業(yè)智能聯(lián)合實(shí)驗(yàn)室執(zhí)行主任、國(guó)家杰出青年科學(xué)基金獲得者、四川省特聘專家、四川省統(tǒng)計(jì)專家咨詢委員會(huì)委員。主要從事“超高維數(shù)據(jù)分析”和“高頻金融數(shù)據(jù)分析”兩個(gè)領(lǐng)域的研究。

甘肅應(yīng)用數(shù)學(xué)中心

甘肅省高校應(yīng)用數(shù)學(xué)與復(fù)雜系統(tǒng)省級(jí)重點(diǎn)實(shí)驗(yàn)室

蘭州大學(xué)大數(shù)據(jù)科學(xué)研究中心

yl7703永利官網(wǎng)

蘭州大學(xué)萃英學(xué)院

2023年3月3日