MoonKnight
  • Member for 10 years, 2 months
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  • London, United Kingdom
What's the intuition behind the estimation of Q, R in a scalar (one-dimension) Kalman Filter
Accepted answer
4 votes

I will be relatively crude with my explanation in an attempt to forego some mathematical nuances. Here I will assume that your state space model is the general linear Gaussian one and that $$y_{t} = ...

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State space model with regression effects
Accepted answer
3 votes

The way this is done, is to first establish the relationship between $\alpha_{t}$ and $\alpha_{t}^{\ast}$ and proceed from there. We take the initial state equations above and take $$\alpha_{t}^{\ast}...

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Does an accurate "noise" model help when using a Kalman filter?
2 votes

Here I will assume that your state space model is the general linear Gaussian one and that $$y_{t} = Z_{t}\alpha_{t} + \epsilon_{t}, \;\;\;\;\;\; \epsilon_{t} \sim N(0, H_{t}),$$ and $$\alpha_{t + ...

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Noise identification in Kalman filtering procedure
0 votes

A straight forward Kalman Filter can handle this right out of the box. The 1D model you describe is the univariate model and your implementation of the Kalman Filter would merely keep the time-stamp ...

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