likelihood function
Computation of the Full Likelihood Function for Estimating Variance at a Quantitative Trait Locus
... The conventional method of QTL variance analysis maximizes the likelihood function by replacing the missing IBDs by their conditional expectations (the expectation met[r] ...
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Reconstruction of stochastic nonlinear models from trajectory measurements
... a likelihood function written in the form of a path-integral over stochastic system trajectories, properly accounting for the Jacobian prefactor term that optimally compensates for dynamical noise; (ii) a ...
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4751.pdf
... Confidence regions and fungible parameter values are similar in that they com- municate parameter uncertainty and are both computed directly from the likelihood function. Due to these commonalities, we set ...
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Remarks on drift estimation for diffusion processes
... maximum likelihood principle to the path-space density of the desired model equations, and through knowledge of the properties of quadratic ...(singular) likelihood function for the ...
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Modeling Expectations with Noncausal Autoregressions
... plicated empirical issue than in conventional causal autoregressions. Which model is selected is also of great economic interest, as it tells us to what extent the economic variable depends on its past and expected ...
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Optimal discrete stopping times for reliability growth tests
... Figure 1 illustrates the locus of points for p and j where the expectation of Eq. (14) is less than 0. We see that there is an inverse relation between the number of tests and the efficacy of the testing, if p is large ...
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Solar Radiation Polyhedron Sensor with Self-calibration Facility
... the likelihood function given the radiation of surfaces (observations) and the current estimate of the angles of surfaces (unknown parameters), while the M (maximization) step computes new estimates by ...
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Testing for predictability in a noninvertible ARMA model
... density function of a conventional invert- ible ARMA(1,1) process with the same parameter values as in ...density function and, hence, by the autocovariance ...Gaussian likelihood function of ...
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Significance Tests for Binomial Experiments: Ordering the Sample Space by Bayes Factors and Using Adaptive Significance Levels for Decisions
... Keywords: Significance level, sample size, Bayes ratio, likelihood function, optimal decision, 22.. significance test.[r] ...
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Bayesian Modeling for the Remanufacturing and Reuse of Components for the Reduction of Costs in a Line of Printing Products
... The components in the Bayes model will be substantiated, that is, the a priori distributions for the parameters, the likelihood function, the marginal distribution and the posteriori distribution, with ...
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Bayesian Multiperiod Forecasting for Arma Model under Jeffrey's Prior
... model, likelihood function, Jeffrey’s prior, posterior distribution, Bayes theorem, conditional predictive density, conditional posterior predictive density, marginal conditional posterior predictive ...
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Learning in Neural Spatial Interaction Models: A Statistical Perspective
... objective function is defined by the negative log-likelihood function and the search space by the parameter space of an origin constrained product unit neural spatial interaction ...maximum ...
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Autonomous crowds tracking with box particle filtering and convolution particle filtering
... Autonomous systems such as Unmanned Aerial Vehicles (UAVs) need to be able to recognise and track crowds of people, e.g. for rescuing and surveillance purposes. Large groups generate multiple measurements with uncertain ...
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Discrete measurement, continuous time and event history modeling
... The likelihood-functions presented above need to be augmented to accommodate right-censored ...the likelihood function is the survival distribution (S()) evaluated at time ...the likelihood ...
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Graph matching with a dual-step EM algorithm
... Our aim is to extract geometric transformation parameters and correspondence matches from the two point-sets using the EM algorithm. When couched probabilistically, the goal can be succinctly stated as that of jointly ...
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The Dual of the Maximum Likelihood
... the likelihood function would be modified in the amount equal to the value of the Lagrange multiplier per unit value increase (or decrease) in the level of the corresponding sample ...objective ...
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Dubbert, Joerg (2001): Measurement of the W Boson Mass in the W+W-->qqlv Channel with the OPAL Detector at LEP. Dissertation, LMU München: Fakultät für Physik
... physics function makes the use of constant widths determined from Monte Carlo as in the Breit-Wigner fit unnecessary and leads to a reduction of the bias correc- ...maximum likelihood fit improves the ...
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The relation between insulin resistance and lung function: a cross sectional study
... lung function seems notable and supports the suggestion that the metabolic pathways related to insulin resistance are crucial in initi- ating lung abnormalities in type 2 diabetic patients ...the likelihood ...
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Pituitary abscess: a case report and review of the literature
... In conclusion, this case report highlights the importance of early diagnosis and appropriate management of a pituitary abscess. The diagnosis in most cases is extremely difficult before surgery, due to overlapping ...
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A Generalized Gamma-Weibull Distribution: Model, Properties and Applications
... where ( ) g x is pdf corresponding to G x ( ) . The rest of the paper is organized as follows. In section 2, the Gamma-Weibull distribution is introduced. Properties of this distribution are obtained in Section 3. In ...
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