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As a part of #193 I already made some changes, so I wanted to get the feedback from maintainers about it.
Plus, there are a few other changes in the same direction that I can integrate into #193, so I wanted to mention them here too.
- Parameters. Sometimes they are called parameters, sometimes identifiers (in the ParTable).
I propose to change it intoparam
(intuitively understandable, but still short):param
in the ParTableparams()
to get the vector of parametersnparams()
to get the number of parameters (calledn_par()
now)
- Variables. Sometimes called vars, sometimes colnames, sometimes nodes.
Observed variables are sometimes called observed, sometimes manifested.
I propose to consolidate into vars (short, but intuitive), which could be observed (more intuitive than manifested) or latent:vars()
to get the vector of variables fromParTable
,RAMMatrices
(matching the order ofA
columns)nvars()
to get the number of variablesobserved_vars()
to get the observed variables matching the order of rows/cols inobs_cov
and rows ofRAMMatrices.F
Alternatively, it could beobs_vars()
, which would matchobs_cov()
andobs_mean()
(ifobserved_vars
is chosen, thenobs_cov
also needs be renamed intoobserved_cov
for consistency).nobserved_vars()
to get the number of observed vars (replacesn_man
, which in this short form is a little bit confusing).latent_var_indices()
/observed_var_indices()
to get the indices ofvars()
that match the observed/latent variables
(i-th index ofobserved_var_indices()
is for the i-th variable ofobserved_vars()
)latent_vars()
is a shortcut tovars()[latent_var_indices()]
- Also, in case of missing data, I propose to use measured/missing terms (now it uses observed/missing, but observed clashes with observed/latent), and nmeasured_vars()/nmissing_vars() to get their counts
- Observations. Also referred to as rows. To disambiguate from observed_vars, I propose to refer to as samples (row is confusing because SEM operates with so many matrices).
samples
to access to the individual samples (sometimes referred to asrows
orrowwise
).nsamples()
is the number of samples (n_obs()
now)
- Relations (between the variables, i.e.
<-
or<->
). Now theParTable
have the inparam_type
column, which is confusing, because sometimes it is constant.
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