algebraic.mle 0.9.0
- Initial CRAN release
- Core MLE class (
mle) with methods for:
- Parameter extraction (
params,
nparams)
- Variance-covariance (
vcov, se)
- Confidence intervals (
confint)
- Model comparison (
aic, loglik_val)
- Bias and MSE estimation (
bias, mse)
- Fisher information (
observed_fim)
- Sampling from MLE distribution (
sampler)
- Predictive intervals (
pred)
- Expected values (
expectation)
- Marginal distributions (
marginal)
- Numerical optimization wrapper (
mle_numerical) for
optim() results
- Bootstrap MLE (
mle_boot) for small samples
- MLE transformations via invariance property (
rmap)
- Weighted combination of MLEs (
mle_weighted)
- Three vignettes demonstrating usage:
- Fitting common distributions to a DGP
- Statistics and characteristics of the MLE
- Data generating processes