Time series are data observed over time (either in continuous time or at discrete time periods).

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Help in State and parameter estimation for a time series model excited by binary input

An IIR system is excited by a pseudorandom binary signal $z_n$. The output of the system is corrupted by zero mean additive white Gaussian noise and this is observed, i.e., $y_n = \mathbf{h^Ty_{n-1}} ...
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Beginner level: Help in learning Kalman Smoother (Part 1)

Parameter estimation of Linear Dynamical system is a tutorial which explains Kalman Filter, Smoothing, and Expectation Maximization. I have followed the derivation for Kalman Filter. But cannot ...
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How to use lagged dependent variables (panel data) in practice?

Working with a panel data set with a daily time series structure I was told to include a lagged dependent variable. The dependent variable is daily electricity consumption of a medium size sample ...