Estimate Concentrated log likelihood function for local level model

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I have a project in R but i face some difficulties. I actually want to run a local level model for the growth rate of deaths of a pandemic without using structTS or any other ready package for time series models. I want to find the forecast error using the kalman filter and smoother and take these as an input for a regression that i want to run. Bellow you can see the code for the kalman filter that i have already wrote but I don't know how to initialize the variances of the state and the observation equation. In Nile river data of Durbin and Koopman they start with the estimations which are obtained by maximizing the concentrated log likelihood function. You can see in the photos what I mean. The initial values of var epsilon and var eta are 15099 and 1469. For the data that I have I want to estimate the var epsilon and the q as stated in the photo and then use these intializations as input for the kalman filter and smoother. So does any of you has an idea of how to estimate the q in R using the 2.63 concentrated log likelihood function? Thank you for your time.

数据科学 R 编程语言 统计学 统计分析 数学

项目ID: #26790485

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