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