Suppose we are interested in modeling a response (Y) as a linear function of some covariates (X's) based on a set of observations. As you know, it can easily be done by the linear regression method. Now consider a more complicated setting, where Y is not a scalar (a single value), but it is a high-dimensional functional (profile) data. In this case, the response for ith sample is represented as a vector yi=[y11,yi2,,y10000]T. If you were to model and solve this problem, how would you approach it? In addition to describing your methodology, you should provide the list of references (papers or books) you may use in developing your methodologies. Please limit your answer to one page (excluding the list of reference). Suppose we are interested in modeling a response (Y) as a linear function of some covariates (X's) based on a set of observations. As you know, it can easily be done by the linear regression method. Now consider a more complicated setting, where Y is not a scalar (a single value), but it is a high-dimensional functional (profile) data. In this case, the response for ith sample is represented as a vector yi=[y11,yi2,,y10000]T. If you were to model and solve this problem, how would you approach it? In addition to describing your methodology, you should provide the list of references (papers or books) you may use in developing your methodologies. Please limit your answer to one page (excluding the list of reference)