We present a procedure to monitor the structural changes in the penalized regression model for high-dimensional data sequentially. Our approach utilizes a given historical data set to perform both variable selection and estimation simultaneously. Te asymptotic properties of the test statistics are established underthe null and alternative hypotheses. The finite sample behaviorof the monitoring procedure is investigated with simulation studies. The proposed method is applied to a real data set to illustrate the detection procedure.
