Evaluation of thresholding methods for activation likelihood estimation meta‐analysis via large‐scale simulations
Sign Up to like & getrecommendations! Published in 2022 at "Human Brain Mapping"
DOI: 10.1002/hbm.25898
Abstract: In recent neuroimaging studies, threshold‐free cluster enhancement (TFCE) gained popularity as a sophisticated thresholding method for statistical inference. It was shown to feature higher sensitivity than the frequently used approach of controlling the cluster‐level family‐wise… read more here.
Keywords: meta analysis; likelihood estimation; level; correction ... See more keywords
Uncovering neural distinctions and commodities between two creativity subsets: A meta‐analysis of fMRI studies in divergent thinking and insight using activation likelihood estimation
Sign Up to like & getrecommendations! Published in 2022 at "Human Brain Mapping"
DOI: 10.1002/hbm.26029
Abstract: The dual‐process theory that two different systems of thought coexist in creative thinking has attracted considerable attention. In the field of creative thinking, divergent thinking (DT) is the ability to produce multiple solutions to open‐ended… read more here.
Keywords: divergent thinking; insight; likelihood estimation; activation likelihood ... See more keywords
Trends in the sample size, statistics, and contributions to the BrainMap database of activation likelihood estimation meta‐analyses: An empirical study of 10‐year data
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DOI: 10.1002/hbm.26177
Abstract: The literature of neuroimaging meta‐analysis has been thriving for over a decade. A majority of them were coordinate‐based meta‐analyses, particularly the activation likelihood estimation (ALE) approach. A meta‐evaluation of these meta‐analyses was performed to qualitatively… read more here.
Keywords: sample size; likelihood estimation; meta analyses; meta ... See more keywords
Robust group variable screening based on maximum Lq-likelihood estimation.
Sign Up to like & getrecommendations! Published in 2021 at "Statistics in medicine"
DOI: 10.1002/sim.9212
Abstract: Variable screening plays an important role in ultra-high-dimensional data analysis. Most of the previous analyses have focused on individual predictor screening using marginal correlation or other rank-based techniques. When predictors can be naturally grouped, the… read more here.
Keywords: likelihood estimation; estimation; variable screening; maximum likelihood ... See more keywords
Targeted maximum likelihood estimation of causal effects with interference: A simulation study
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DOI: 10.1002/sim.9525
Abstract: Interference, the dependency of an individual's potential outcome on the exposure of other individuals, is a common occurrence in medicine and public health. Recently, targeted maximum likelihood estimation (TMLE) has been extended to settings of… read more here.
Keywords: targeted maximum; likelihood estimation; interference; maximum likelihood ... See more keywords
Implementing Maximum Likelihood Estimation of Empirical Matching Models
Sign Up to like & getrecommendations! Published in 2020 at "Computational Economics"
DOI: 10.1007/s10614-020-10072-8
Abstract: We propose two Mathematical Programming with Equilibrium Constraints (MPEC) formulations: the MPEC-Sparse and the MPEC-Dense to estimate a class of separable matching models. We compare MPEC with the Nested Fixed-Point (NFXP) algorithm—a well-received method in… read more here.
Keywords: likelihood estimation; matching models; maximum likelihood; matching ... See more keywords
Maximum Likelihood Estimation Methods for Copula Models
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DOI: 10.1007/s10614-021-10139-0
Abstract: For Copula models, the likelihood function could be multi-modal, and some traditional optimization algorithms such as simulated annealing (SA) may get stuck in the local mode and introduce bias in parameter estimation. To address this… read more here.
Keywords: likelihood estimation; estimation; estimation methods; maximum likelihood ... See more keywords
Penalized quasi-maximum likelihood estimation for extreme value models with application to flood frequency analysis
Sign Up to like & getrecommendations! Published in 2020 at "Extremes"
DOI: 10.1007/s10687-020-00379-y
Abstract: A common statistical problem in hydrology is the estimation of annual maximal river flow distributions and their quantiles, with the objective of evaluating flood protection systems. Typically, record lengths are short and estimators imprecise, so… read more here.
Keywords: likelihood estimation; quasi maximum; maximum likelihood; penalized quasi ... See more keywords
Tumor growth modeling: Parameter estimation with Maximum Likelihood methods
Sign Up to like & getrecommendations! Published in 2018 at "Computer methods and programs in biomedicine"
DOI: 10.1016/j.cmpb.2018.03.014
Abstract: BACKGROUND & OBJECTIVE In this work, we focus on estimating the parameters of the widely used Gompertz tumor growth model, based on measurements of the tumor's volume. Being able to accurately describe the dynamics of… read more here.
Keywords: likelihood estimation; estimation; maximum likelihood; growth ... See more keywords
Grain size estimation in polycrystals: Solving the corpuscle problem using Maximum Likelihood Estimation
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Structural Geology"
DOI: 10.1016/j.jsg.2021.104418
Abstract: Abstract In materials science, the microstructures of materials are generally characterized by 2D observation (e.g. electron microscopy). For polycrystalline materials, such as crystalline rocks or ceramics, those observations can be used to measure the grain… read more here.
Keywords: maximum likelihood; grain size; estimation; likelihood estimation ... See more keywords
Quasi-likelihood estimation of structure-changed threshold double autoregressive models
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Statistical Planning and Inference"
DOI: 10.1016/j.jspi.2019.06.008
Abstract: Abstract This paper investigates the quasi-maximum likelihood estimator (QMLE) of the structure-changed and two-regime threshold double autoregressive model. It is shown that both the estimated threshold and change-point are n -consistent, and they converge weakly… read more here.
Keywords: threshold double; double autoregressive; structure changed; likelihood estimation ... See more keywords