Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies ↑の最後に、Rのプログラムがある。 2009年の時点ですでにRとはかなり先取りな感じですね・・。 ぐぐったら、ハバ大のコロ助さんも出てきた 機械学習をつかったセミパラメトリック推定 ...

Abstract: Over the past few decades, numerous adaptive Kalman filters (AKFs) have been proposed. However, achieving online estimation with both high estimation accuracy and fast convergence speed is ...

Abstract: This work presents a maximum likelihood estimation algorithm for optical pathlength in spectral interferometry (SI) that achieves the shot-noise-limited Cramér–Rao bound (CRB) of estimator ...

Relatedness between individuals is central to ecological genetics. Multiple methods are available to quantify relatedness from molecular data, including method-of-moment and maximum-likelihood ...

Understanding how functional connectivity between cortical neurons varies with spatial distance is crucial for characterizing large-scale neural dynamics. However, inferring these spatial patterns is ...

There are three SAS procedures that enable you to do maximum likelihood estimation of parameters in an arbitrary model with a likelihood function that you define: PROC MODEL, PROC NLP, and PROC IML.