Release 0.5.0#330
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* convert to argument type-dependent dispatch * replace start_val() function with prepare_start_params() * refactor start_parameter_table() into prepare_start_params(start_val::ParameterTable, ...) and use the SEM model param indices * unify processing of starting values by all optimizers * support dictionaries of values
Co-authored-by: Maximilian Ernst <34346372+Maximilian-Stefan-Ernst@users.noreply.github.com>
NLopt minimum was 18.11, below what the test expected
Support optimization backends via package extensions
define a single source_to_dest_perm() function
reduces code duplication; also annotate types of ctor args now samples(SemObsCov) returns nothing
add observed_vars(data::SemObserved)
* use SemObsMissingPattern struct to
simplify code
* replace O(Nvars^2) common pattern detection
with Dict{}
* don't store row-wise, store sub-matrices
of non-missing data instead
* use StatsBase.mean_and_cov()
StatsBase.mean_and_cov() is used instead
- SemObservedData: parameterize by cov/mean eltype instead of the whole container types Co-authored-by: Maximilian Ernst <34346372+Maximilian-Stefan-Ernst@users.noreply.github.com>
to match the update data preparation behaviour
to specify the prefix of the generated observed_vars if none provided could be inferred, defaults to :obs
Co-authored-by: Copilot <copilot@github.com>
to allow replicating the whole refloss state, e.g. for replace_observed() Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <copilot@github.com>
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