Hello,
Please have a look at Figure 5 of Czekala et al. 2015:
It explains how the addition of local kernel can be so useful in some cases. My question is: how can I add an outlier line (for example, 5202.2 Angestrum) into code?
As the Starfish documentation says, I have to define its kernel by its hyperparameters:
log_amp: The natural logarithm of the amplitude of the kernel
mu: The location of the local kernel
log_sigma: The natural logarithm of the standard deviation of the kernel
Does it mean that I use the following definition in the SpectrumModel function as:
local_cov = dict(log_amp:?, mu: 5202.2, log_sigma:?)
If yes, please guide me on how to select "log_amp" and "log_sigma". Does "mu" value is correct?
And how to define them in the prior values:
"local_cov:log_amp": st.norm(?),
"local_cov:log_sigma": st.norm(?),
"local_cov:mu": st.norm (5222.1, 0.1)
Thanks a lot for any help in advance.
Hello,
Please have a look at Figure 5 of Czekala et al. 2015:
It explains how the addition of local kernel can be so useful in some cases. My question is: how can I add an outlier line (for example, 5202.2 Angestrum) into code?
As the Starfish documentation says, I have to define its kernel by its hyperparameters:
log_amp: The natural logarithm of the amplitude of the kernel
mu: The location of the local kernel
log_sigma: The natural logarithm of the standard deviation of the kernel
Does it mean that I use the following definition in the SpectrumModel function as:
local_cov = dict(log_amp:?, mu: 5202.2, log_sigma:?)
If yes, please guide me on how to select "log_amp" and "log_sigma". Does "mu" value is correct?
And how to define them in the prior values:
"local_cov:log_amp": st.norm(?),
"local_cov:log_sigma": st.norm(?),
"local_cov:mu": st.norm (5222.1, 0.1)
Thanks a lot for any help in advance.