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Found 5 papers, 2 papers with code
Estimating granular house price distributions in the Australian market using Gaussian mixtures
Price indices are derived as means, medians, quantiles or other functions of the estimated distributions.
Bayesian Forecasting in Economics and Finance: A Modern Review
The Bayesian statistical paradigm provides a principled and coherent approach to probabilistic forecasting.
Optimal reconciliation with immutable forecasts
In this paper, we formulate reconciliation methodology that keeps forecasts of a pre-specified subset of variables unchanged or "immutable".
Computationally Efficient Learning of Statistical Manifolds
By exploiting the connection between Hellinger/total variation distance for discrete distributions and the L2/L1 norm, we demonstrate that the proposed distance estimators, combined with approximate nearest neighbor searching, could largely improve the computational efficiency with little to no loss in the accuracy of manifold embedding.
Updating Variational Bayes: Fast sequential posterior inference
Variational Bayesian (VB) methods produce posterior inference in a time frame considerably smaller than traditional Markov Chain Monte Carlo approaches.
