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 ...

A random sample of curves can be usually thought of as noisy realisations of a compound stochastic process X(t) = Z{W(t)}, where Z(t) produces random amplitude variation and W(t) produces random ...

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 ...

Abstract: In high-energy calorimetry, energy estimation is typically carried out using digital linear filters, from which the amplitude of a conditioned signal is inferred. The linear design is ...

We present a maximum-likelihood method for parameter estimation in terahertz time-domain spectroscopy. We derive the likelihood function for a parameterized frequency response function, given a pair ...

In certain multivariate problems the full probability density has an awkward normalizing constant, but the conditional and/or marginal distributions may be much more tractable. In this paper we ...

Abstract: Independence of the normalized likelihood functions (likelihood ratios, LR) with the argument being the true Toeplitz covariance matrix creates a statistical lower bound for the optimized ...

Identify characteristics of “good” estimators and be able to compare competing estimators. Construct sound estimators using the techniques of maximum likelihood and method of moments estimation.