重慶大學(xué)數(shù)學(xué)與統(tǒng)計(jì)學(xué)院開設(shè)了一場題為“Model and Feature Selection in A Class of Semiparametric Models(型號(hào)和特性選擇在半?yún)��?shù)模型的A級(jí))”的講座，重慶大學(xué)數(shù)學(xué)與統(tǒng)計(jì)學(xué)院目前設(shè)有數(shù)學(xué)系、信息與計(jì)算科學(xué)系、統(tǒng)計(jì)與精算系，分別負(fù)責(zé)三個(gè)本科專業(yè)——數(shù)學(xué)與應(yīng)用數(shù)學(xué)、信息與計(jì)算科學(xué)、統(tǒng)計(jì)學(xué)的建設(shè)與人才培養(yǎng)。講座的主要內(nèi)容是：

　　選型是一首老歌統(tǒng)計(jì)。隨著高維近年來激增，人們開始用新的調(diào)----的懲罰似然法進(jìn)行播放。在這次演講中，Wenyang Zhang教授要研究一類半?yún)��?shù)模型的，潛在的解釋變量數(shù)量的增長比樣品尺寸要快。Wenyang Zhang要禮物選擇的重要特征，同時(shí)確定了正確的模型的新懲罰的可能性程序。我將探討建議的程序處罰部分的有效性，并提出把罰款的新途徑。漸近性質(zhì)將提交證明擬議的方法。我也表明了該程序的性能時(shí)，樣本規(guī)模是模擬研究有限。最后，Wenyang Zhang將用真實(shí)數(shù)據(jù)的例子說明了該方法的應(yīng)用。

　　原文：Model selection is an old song in statistics. With the surge of high dimensionality in recent years, people start to play it with a new tune ----the penalised likelihood method. In this talk, I am going to investigate a class of semiparametric models where the number of potential explanatory variables grows much fast than the sample size. I am going present a new penalised likelihood procedure which selects the important features and identifies the correct model simultaneously. I will explore the effectiveness of the penalty part in the proposed procedure, and present a new way to put penalty. Asymptotic properties will be presented to justify the proposed methodology. I will also show the performance of the proposed procedure when sample size is finite by simulation studies. Finally, I will illustrate the application of the proposed method by a real data example.