scholarly journals A likelihood analysis of quantile-matching transformations

Biometrika ◽  
2020 ◽  
Author(s):  
P McCullagh ◽  
M F Tresoldi
Keyword(s):  
Linear Model ◽  
Profile Likelihood ◽  
Monotone Transformation ◽  
Target Distribution ◽  
Likelihood Analysis ◽  
Model Setting

Summary Quantile matching is a strictly monotone transformation that sends the observed response values to the quantiles of a given target distribution. A profile likelihood-based criterion is developed for comparing one target distribution with another in a linear-model setting.

scholarly journals Quantification of oxygen metabolic rates in Human brain with dynamic 17 O MRI: Profile likelihood analysis

2016 ◽  
Vol 78 (3) ◽  
pp. 1157-1167 ◽  
Author(s):  
Dmitry Kurzhunov ◽  
Robert Borowiak ◽  
Helge Hass ◽  
Philipp Wagner ◽  
Axel Joachim Krafft ◽  
...  
Keyword(s):  
Human Brain ◽  
Profile Likelihood ◽  
Metabolic Rates ◽  
Likelihood Analysis

A dynamic growth model of Dunaliella salina : Parameter identification and profile likelihood analysis

2014 ◽  
Vol 173 ◽  
pp. 21-31 ◽  
Author(s):  
Melanie Fachet ◽  
Robert J. Flassig ◽  
Liisa Rihko-Struckmann ◽  
Kai Sundmacher
Keyword(s):  
Parameter Identification ◽  
Growth Model ◽  
Dunaliella Salina ◽  
Profile Likelihood ◽  
Likelihood Analysis ◽  
Dynamic Growth

scholarly journals A profile likelihood analysis of the constrained MSSM with genetic algorithms

2010 ◽  
Vol 2010 (4) ◽  
Author(s):  
Yashar Akrami ◽  
Pat Scott ◽  
Joakim Edsjö ◽  
Jan Conrad ◽  
Lars Bergström
Keyword(s):  
Genetic Algorithms ◽  
Profile Likelihood ◽  
Likelihood Analysis

scholarly journals Profile likelihood analysis for a stochastic model of diffusion in heterogeneous media

2021 ◽  
Vol 477 (2250) ◽  
pp. 20210214
Author(s):  
Matthew J. Simpson ◽  
Alexander P. Browning ◽  
Christopher Drovandi ◽  
Elliot J. Carr ◽  
Oliver J. Maclaren ◽  
...  
Keyword(s):  
Stochastic Model ◽  
Heterogeneous Media ◽  
Profile Likelihood ◽  
Absorbing Boundary ◽  
One Dimensional ◽  
Likelihood Analysis ◽  
Approximate Likelihood ◽  
Profile Likelihoods ◽  
Parameter Values ◽  
The Continuum

We compute profile likelihoods for a stochastic model of diffusive transport motivated by experimental observations of heat conduction in layered skin tissues. This process is modelled as a random walk in a layered one-dimensional material, where each layer has a distinct particle hopping rate. Particles are released at some location, and the duration of time taken for each particle to reach an absorbing boundary is recorded. To explore whether these data can be used to identify the hopping rates in each layer, we compute various profile likelihoods using two methods: first, an exact likelihood is evaluated using a relatively expensive Markov chain approach; and, second, we form an approximate likelihood by assuming the distribution of exit times is given by a Gamma distribution whose first two moments match the moments from the continuum limit description of the stochastic model. Using the exact and approximate likelihoods, we construct various profile likelihoods for a range of problems. In cases where parameter values are not identifiable, we make progress by re-interpreting those data with a reduced model with a smaller number of layers.

scholarly journals Hands on XENON-100: background and signal modeling and profile likelihood analysis

2015 ◽  
Author(s):  
Brett Cornell ◽  
Barbara Rosario Montes Nunez ◽  
Ferella Davide Alfredo
Keyword(s):  
Profile Likelihood ◽  
Signal Modeling ◽  
Hands On ◽  
Likelihood Analysis
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