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Efficiency in indirect inference
2010We extend the method of indirect inference by using \emph{non-parametric} auxiliary models of densities. Suppose we observe i.i.d.~random variables $X_{1},\ldots,X_{n}$ and are given a (possibly misspecified) parametric model with parameter set $\Theta\subseteq\mathbb{R}^{m}$.
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Gene regulatory network inference in the era of single-cell multi-omics
Nature Reviews Genetics, 2023Pau Badia-i-Mompel +2 more
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Indirect inference under stochastic restrictions
2003This paper investigates inference methods to introduce prior information in econometric modelling. The set up includes the nonlinear least squares and indirect inference estimators. The goal is to show that stochastic restrictions method estimates can be asymptotically more efficient than estimates ignoring prior information and can achieve efficiency ...
J.A. Hernández Sánchez +1 more
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Inference in artificial intelligence with deep optics and photonics
Nature, 2020Gordon Wetzstein +2 more
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IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era
Molecular Biology and Evolution, 2020Bui Quang Minh +2 more
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Causal inference for time series
Nature Reviews Earth & Environment, 2023Jakob Runge, Gherardo Varando
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Multi-omics single-cell data integration and regulatory inference with graph-linked embedding
Nature Biotechnology, 2022Zhi-Jie Cao, Ge Gao
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Contextual inference underlies the learning of sensorimotor repertoires
Nature, 2021James B Heald +2 more
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Advantages and limitations of current network inference methods
Nature Reviews Microbiology, 2010Riet De Smet, Kathleen Marchal
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