[R] Evaluating/comparing dynamic linear model

R_help Help rhelpacc at gmail.com
Thu Oct 8 02:55:22 CEST 2009


I have two DLM model specifications (x[t] and y[t] are univariate):

y[t] = b[t]x[t]+e[t], e[t] ~ N(0,v1^2)
b[t] = b[t-1]+eta[t], eta[t] ~ N(0,w1^2)

y[t] = a[t]+e[t], e[t] ~ N(0,v2^2)
a[t] = a[t-1]+eta[t], eta[t] ~ N(0,w2^2)

I run the filter through data recursively to obtain state variables
for each model. However, how do I know if b[t]x[t] in MODEL1 is
different from MODEL2? In other words, how do I know if x[t] makes a
difference in explaining dynamic of y[t]?

Another question is that how do I compare MODEL1 and MODEL2? From
model specification point of view, how can one say that MODEL1 is
better than MODEL2? Any suggestion/reference would be greatly
appreciated. Thank you.


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