Results 11 to 20 of about 1,079,892 (278)

A Nonparametric Bayesian Approach to the Rare Type Match Problem

Entropy, 2020
The “rare type match problem” is the situation in which, in a criminal case, the suspect’s DNA profile, matching the DNA profile of the crime stain, is not in the database of reference.
Giulia Cereda, Richard D. Gill
doaj   +3 more sources

Adjusted Versions of Profile Likelihood and Directed Likelihood, and Extended Likelihood

Journal of the Royal Statistical Society Series B: Statistical Methodology, 1994
SUMMARY Several adjusted and invariant versions of profile likelihood and of directed likelihood (short for signed log-likelihood ratio) are discussed. These adjusted versions, which fall into two groups, are closely related to modified profile likelihood and modified directed likelihood.
openaire   +5 more sources

Hierarchical Generalized Linear Models: The R Package HGLMMM [PDF]

Journal of Statistical Software, 2011
The R package HGLMMM has been developed to fit generalized linear models with random effects using the h-likelihood approach. The response variable is allowed to follow a binomial, Poisson, Gaussian or gamma distribution.
Marek Molas, Emmanuel Lesaffre
doaj   +1 more source

Uncertainty components in profile likelihood fits

European Physical Journal C: Particles and Fields
When a measurement of a physical quantity is reported, the total uncertainty is usually decomposed into statistical and systematic uncertainties. This decomposition is not only useful for understanding the contributions to the total uncertainty, but is ...
Andrés Pinto, Zhibo Wu, Fabrice Balli, Nicolas Berger, Maarten Boonekamp, Émilien Chapon, Tatsuo Kawamoto, Bogdan Malaescu   +7 more
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Latent profile analysis of uncertainty in illness and eating self-efficacy in patients with gastric cancer and its associated factors: a cross-sectional study [PDF]

Frontiers in Public Health
BackgroundPatients with gastric cancer frequently experience substantial psychological burden throughout diagnosis and treatment. Uncertainty in illness and eating self-efficacy are two key determinants of psychological adjustment and rehabilitation ...
Minyi Shi, Minyi Shi, Chengxi Xia, Yuxin Ye, Yuxin Ye   +4 more
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Optimal Experimental Design Based on Two-Dimensional Likelihood Profiles

Frontiers in Molecular Biosciences, 2022
Dynamic behavior of biological systems is commonly represented by non-linear models such as ordinary differential equations. A frequently encountered task in such systems is the estimation of model parameters based on measurement of biochemical compounds.
Tim Litwin, Tim Litwin, Tim Litwin, Jens Timmer, Jens Timmer, Jens Timmer, Clemens Kreutz, Clemens Kreutz, Clemens Kreutz   +8 more
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Estimating uncertainty of model parameters obtained using numerical optimisation [PDF]

Modeling, Identification and Control, 2019
Obtaining accurate models that can predict the behaviour of dynamic systems is important for a variety of applications. Often, models contain parameters that are difficult to calculate from system descriptions.
Ole Magnus Brastein, Bernt Lie, Carlos F. Pfeiffer, Nils-Olav Skeie   +3 more
doaj   +1 more source

Bayesian Inference in Extremes Using the Four-Parameter Kappa Distribution

Mathematics, 2020
Maximum likelihood estimation (MLE) of the four-parameter kappa distribution (K4D) is known to be occasionally unstable for small sample sizes and to be very sensitive to outliers.
Palakorn Seenoi, Piyapatr Busababodhin, Jeong-Soo Park   +2 more
doaj   +1 more source

Likelihood-based estimation and prediction for a measles outbreak in Samoa

Infectious Disease Modelling, 2023
Prediction of the progression of an infectious disease outbreak is important for planning and coordinating a response. Differential equations are often used to model an epidemic outbreak's behaviour but are challenging to parameterise. Furthermore, these
David Wu, Helen Petousis-Harris, Janine Paynter, Vinod Suresh, Oliver J. Maclaren   +4 more
doaj   +1 more source

PROLIFIC: A Fast and Robust Profile-Likelihood-Based Muscle Onset Detection in Electromyogram Using Discrete Fibonacci Search

IEEE Access, 2020
A stochastic scheme, namely, PLM-Lap, has recently been propounded, which relies on the profile likelihood (PL) constructed with a Laplace distribution for estimating muscle activation onsets (MAOs) in surface electromyographic (sEMG) data.
Easter S. Suviseshamuthu, Didier Allexandre, Umberto Amato, Biancamaria Della Vecchia, Guang H. Yu   +4 more
doaj   +1 more source