Refactor Sem multi-group support

[alyst]

This is a largest remaining part of #193, which changes some interfaces.

Refactoring of the SEM types

• AbstractLoss is the base type for all functions
• SemLoss{O,I} <: AbstractLoss is the base type for all SEM losses, it now requires to have observed::O and implied::I field
• Since SemLoss ctor should always be given observed and implied (positional), meanstructure keyword is gone -- loss should always respect implied specification.
• LossTerm is a thin wrapper around AbstractLoss that adds optional id of the loss term and optional weight
• Sem is a container of LossTerm objects (accessible via loss_terms(sem), or loss_term(sem, id)), so it can handle multiple SEM terms (accessible via sem_terms(sem) -- subset of loss_terms(sem), or sem_term(sem, id)).
  It replaces both the old Sem and SemEnsemble.
• AbstractSingleSem, AbstractSemCollection and SemEnsemble are gone.

Method changes

Multi-term SEMs could be created like

model = Sem(
    :Pasteur => SemML(obs_g1, RAMSymbolic(specification_g1)),
    :Grant_White => SemML(obs_g2, RAM(specification_g2)),
    ...
)

Or with weights specification

model = Sem(
    :Pasteur => SemML(obs_g1, RAMSymbolic(specification_g1)) => 0.5,
    :Grant_White => SemML(obs_g2, RAM(specification_g2)) => 0.6,
)

The new Sem() and loss-term constructors rely less on keyword arguments and more on positional arguments, but some keywords support is present.

• update_observed!() was removed. It was only used by replace_observed(),
  but otherwise in-place model modification with unclear semantics is error-prone.
• replace_observed(sem, data) was simplified by removing support of additional keywords or requirement to pass SEM specification.
  It only creates a copy of the given Sem with the observed data replaced,
  but implied and loss definitions intact.
  Changing observed vars is not supported -- that is something use-case specific
  that user should implement in their code.
• check_single_lossfun() was renamed into check_same_semterm_type() as
  it better describes what it does. If check is successful, it returns the specific
  subtype of SemLoss.
• bootstrap() and se_bootstrap() use bootstrap!(acc::BootstrapAccumulator, ...)
  function to reduce code duplication
• bootstrap() returns BootstrapResult{T} for better type inference
• fit_measures() now also accepts vector of functions, and includes CFI by default (DEFAULT_FIT_MEASURES constant)
• test_fitmeasures() was tweaked to handle more repetitive code: calculating the subset of fit measures, and compairing this subset against lavaan refs, checking for measures that could not be applied to given loss types (SemWLS).

[Maximilian-Stefan-Ernst]

Suggested change

	In this case, [`FiniteDiffWrapper`](@ref) method to generate a wrapper around the specific `SemLoss` term that only uses its objective
	to calculate the gradient using the finite difference approximation.
	In this case, [`FiniteDiffWrapper`](@ref) can be used to generate a wrapper around the specific `SemLoss` term. This wrapper only uses the `LossTerm`s objective, and calculates the gradient using finite difference approximation.

[alyst]

@Maximilian-Stefan-Ernst It might be a nice idea to use copilot for catching typos, incorrect sentences, but also potential bugs.
I cannot select copilot as a reviewer -- I'm not exactly sure why, whether it is the organization/repository-level setting, or it's my status in the repository.
But I'm also fine if SEM.jl is kept AI-free :)

[Maximilian-Stefan-Ernst]

Is there a reason to pass typeof(term1) instead of term1? I personally find the syntax a bit cleaner without the extra typeof call.

[Maximilian-Stefan-Ernst]

Maybe we should throw an error for a Sem with no terms?

[Maximilian-Stefan-Ernst]

I thought this is done in check_semterm_type?

Suggested change

	term1 = _unwrap(loss(terms[1]))
	L = typeof(term1).name
	# check that all SemLoss terms are of the same class (ML, FIML, WLS etc), ignore typeparams
	for (i, term) in enumerate(terms)
	lossterm = _unwrap(loss(term))
	@assert lossterm isa SemLoss
	if typeof(_unwrap(lossterm)).name != L
	@error "SemLoss term #$i is $(typeof(_unwrap(lossterm)).name), expected $L. Heterogeneous loss functions are not supported"
	end
	end