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I have observed in some cases the CRAVA estimated too long wavelet than what we expected. The default wavelet length in CRAVA is 200ms. And the CRAVA estimated wavelet should usually be close to 200ms…
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Hi,
I was using the previous libjson-rpc-cpp in my project WGSLib (https://github.com/gogo40/wgslib) and everything was working correctly. My web client (https://github.com/gogo40/wgslib/blob/master/…
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Write a function to produce these kind of plots (See Gilmour et al. 1997).
They are useful for identifying sources of spatial variation, and for model diagnostics.
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The current variogram estimation is sensitive to outliers. It would be good to implement the method described by http://www.stat.tamu.edu/~genton/1998.G.MG.1.pdf
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I added the likelihoods for each separate vital rate regression, but also kept the "overall" likelihood of N[t,k] ~ dnorm(yCover, varCov). Is this using the data twice? Send email to Tom to ask...?
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Variogram calculation should be a part of karta.vector.stats. This doesn't need to be efficient or scalable - just needs to work for small problems.
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Add an `ExperimentalVariogram` type. `est_variogram()` would then return this type, which would include the number of observations at each lag to facilitate weighted fitting in `fit!()`.