We study a likelihood ratio test for detecting multiple weak changes in the mean of a class of CHARN models. The locally asymptotically normal (LAN) structure of the family of likelihoods under study is established. It results that the test is asymptotically optimal and an explicit form of its asymptotic local power is given as a function of candidates change locations. Weak changes locations estimates are obtained as the time indexes maximizing an estimate of the local power. A simulation study shows the good performance of our methods compared to some CUSUM approaches. Our results are also applied to three sets of real data.

翻译：我们研究一种可能性比率测试,以发现某类CHARN模型平均值的多重微弱变化。确定了研究中的可能性家庭在当地的无常正常结构。结果显示,测试是无现成的最佳,其无现成的当地力量是作为候选人改变地点的函数而给予的。微弱变化地点估计数是作为时间指数获得的,以最大限度地估计当地力量。模拟研究显示,与CUSUM方法相比,我们的方法表现良好。我们的结果也适用于三套真实数据。