combine() now aligns named estimates and their information matrices by
parameter name. Incompatible, duplicate, missing, or partially named
parameters are rejected rather than silently pooling different quantities.
Fully unnamed estimates retain positional matching.combine(list()) now reports that at least one estimate is required.rmap() now forwards transformation arguments to the transformed point
estimate as well as to the variance calculation, for both delta and Monte
Carlo methods.pred() using point estimate instead of random draw for first Monte
Carlo sample, breaking the parameter-uncertainty integrationconfint() ignoring the parm argument. Now honors parameter
subsetting by name or index, matching the stats::confint contract.confint() producing NaN without informative error when
variance-covariance has negative diagonal (bad Hessian). Now gives
actionable error message.combine() giving cryptic "non-conformable arrays" error when MLEs
have different parameter dimensions. Now validates upfront.sampler.mle_fit_boot() unreachable code branch (length(x$t) == 1
is never true for boot objects; corrected to ncol(x$t) == 1L)stud case in confint.mle_fit_boot() switchpoint() references in roxygen and vignette prose (now params())bias.mle_normal vignette example missing ... in method signatureS3 class renamed from "mle" to "mle_fit" to resolve name collision with
stats4::mle (S4 class). Subclasses follow: "mle_fit_numerical",
"mle_fit_boot", "mle_fit_rmap". Constructor function names (mle(),
mle_numerical(), mle_boot()) are unchanged.
Removed aic(), bic(), and loglik_val() generics. Use standard R
generics AIC(), BIC(), and logLik() instead. logLik() returns a
proper "logLik" object with df and nobs attributes, so AIC() and
BIC() work automatically via stats::AIC.default.
Added coef.mle_fit() method delegating to params() for standard R
compatibility.
Removed mle_weighted() constructor and "mle_weighted" class. Use
combine() instead — same inverse-variance weighting with better error
handling and a variadic API.
1:n patterns with seq_len() throughout to avoid edge-case bugspred()"_PACKAGE" sentinel)fixing/ directory (removed dead experimental code)n parameter in rmap()joint() composes independent MLEs with disjoint parameter sets into a
joint MLE with block-diagonal covariance structurecombine() optimally weights independent MLEs for the same parameter via
inverse-variance (Fisher information) weightingas_dist() converts MLE objects to their asymptotic normal distributions,
bridging to the algebraic.dist distribution algebradensity(), cdf(), inv_cdf(),
sup(), dim(), mean(), conditional()rmap() where c() merged parameter names
with transformation output namescoef() S3 method for base R compatibility (delegates to params())logLik() S3 method returning proper logLik object with df and nobs
attributes, enabling automatic AIC() and BIC() support from base Rrmap() to accept numeric n parameter (previously required integer)mle) with methods for:
params, nparams)vcov, se)confint)AIC, logLik)bias, mse)observed_fim)sampler)pred)expectation)marginal)mle_numerical) for optim() resultsmle_boot) for small samplesrmap)mle_weighted)