Results 111 to 120 of about 4,806,885 (346)
Analytical quasi maximum likelihood inference in multivariate volatility models [PDF]
Quasi maximum likelihood estimation and inference in multivariate volatility models remains a challenging computational task if, for example, the dimension is high.
Hafner, C.M., Herwartz, H.
core +1 more source
A maximum likelihood approach to genome assembly [PDF]
, 2022 De novo genome assembly is the bioinformatics' problem to reconstruct the original molecule from its sub-sequences, with no previous knowledge on DNA. Inspired by the maximum likelihood approach, recently a new experimental approach was developed.
Baruzzo, Giacomo
core
FEBS Letters, EarlyView.Inositol pyrophosphates are energy‐rich signaling molecules that perform critical functions in cells. Three different families of phosphatases hydrolyze the β phosphate of the inositol pyrophosphate molecules: two have narrow specificities and one is promiscuous.
Ronda J. Rolfes
wiley +1 more source
Maximum Likelihood Estimation for the Weibull-Burr Distribution
Proceedings of the International Conference on Applied Innovations in ITThis study introduces a new family of distributions known as the five-parameters Weibull- Burr distribution. This study aims to present a new family of Weibull-Burr distributions by utilizing the maximum likelihood estimation (MLE) method to determine ...
Alaa Mohammad, Abbas Kneehr
doaj +1 more source
Maximum Likelihood for Cross-lagged Panel Models with Fixed Effects
Panel Data Econometrics, 2017 Panel data make it possible both to control for unobserved confounders and allow for lagged, reciprocal causation. Trying to do both at the same time, however, leads to serious estimation difficulties.
P. Allison +2 more
semanticscholar +1 more source
Maximum Likelihood Estimation of the Multivariate Normal Mixture Model [PDF]
The Hessian of the multivariate normal mixture model is derived, and estimators of the information matrix are obtained, thus enabling consistent estimation of all parameters and their precisions.
Magnus, Jan R., Boldea, Otilia
core +1 more source
Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
Copula Approximate Bayesian Computation Using Distribution Random Forests
StatsOngoing modern computational advancements continue to make it easier to collect increasingly large and complex datasets, which can often only be realistically analyzed using models defined by intractable likelihood functions.
George Karabatsos
doaj +1 more source
A Maximum Entropy Procedure to Solve Likelihood Equations
Entropy, 2019 In this article, we provide initial findings regarding the problem of solving likelihood equations by means of a maximum entropy (ME) approach. Unlike standard procedures that require equating the score function of the maximum likelihood problem at zero,
Antonio Calcagnì +3 more
doaj +1 more source
Reconstructing enzyme evolution by protein engineering
FEBS Letters, EarlyView.Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler +2 more
wiley +1 more source