Marginal likelihood estimation via harmonic mean
On the use of marginal posteriors in marginal likelihood estimation via importance sampling.
... leaving estimation of univariate marginal posterior densities as the only remaining source of ...estimating marginal probabilities, the approach proposed here is particularly suited for Gibbs ...
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Marginal Likelihood Estimation with the Cross Entropy Method
... In contrast, we use the cross-entropy (CE) method, a versatile adaptive Monte Carlo algo- rithm originally developed for rare-event simulation. The main advantage of the importance sampling approach is that random ...
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Model selection via marginal likelihood estimation by combining thermodynamic integration and gradient matching
... log likelihood landscapes for the exact method and gradient matching are very different, despite the fact that the maximum likelihood configurations match very ...parameter estimation, but not ...
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Maximum likelihood estimation of mean reverting processes
... a mean reverting process starting at a level x(0) = 12, that tends to revert to a level ¯ x = 15, with a speed of reversion η = 4 and a short term standard deviation σ = 5 (one third of the level of ...the ...
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The Composite Marginal Likelihood (CML) Estimation of Panel Ordered-Response Models
... the mean estimates for the ψ and b parameters (in both the MSL and CML cases), but much higher for the l ...the mean finite sample standard error being ...
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Targeted Maximum Likelihood Estimation for Dynamic and Static Longitudinal Marginal Structural Working Models
... the mean of the intervention-specific counterfactual out- come at time t as a function of the interventions through time t, can be used to summarize the effects of these longitudinal ...
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Targeted Maximum Likelihood Estimation for Dynamic and Static Longitudinal Marginal Structural Working Models
... maximum likelihood estimator (TMLE) for the parameters of longitudinal static and dynamic marginal structural ...a marginal structural model is used to model the mean of the ...
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Likelihood Based Estimation of Logistic Structural Nested Mean Models with an Instrumental Variable
... inference via IVs is carried out through a variety of estimands, but typically requires making an additional assumption beyond having a valid ...(1996) via potential outcomes relies on the monotonicity ...
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Estimation of stochastic volatility models via Monte Carlo maximum likelihood
... squared mean indicate pronounced relative strength of the stochastic volatility process while low values of C » signify that the model is close to the one of constant ...
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On Marginal Likelihood Computation in Change-point Models
... The MLL values hardly differ for each K. The posterior central values, standard devia- tions, and 0.25/0.75 quantiles of the main parameters of the best model are reported in Table 4. The posterior medians of the break ...
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On marginal likelihood computation in change-point models
... The MLL values hardly differ for each K. The posterior central values, standard devia- tions, and 0.25/0.75 quantiles of the main parameters of the best model are reported in Table 4. The posterior medians of the break ...
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Empirical likelihood inference for censored median regression model via nonparametric kernel estimation
... empirical likelihood in survival analysis goes back to Thomas and Grunkemeier [37] who derived pointwise confidence intervals for survival function with right censored ...empirical likelihood confidence ...
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On Marginal Quasi-Likelihood Inference in Generalized Linear Mixed Models
... The estimation of the variance component of the random effects in the GLMMs is, however, much more complex as compared to the regression ...the mean vector of the responses is known, these authors use the ...
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Marginal Maximum Likelihood Estimation of Item Response Models in R
... of estimation in IRT and develops R functions utilizing the built-in capabilities of the R environment to find the marginal maximum likelihood estimates of the generalized partial credit ...
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Nonparametric maximum likelihood estimation of the structural mean of a sample of curves
... In contrast, the nonparametric maximum likelihood estimator of Rønn (2001) is √n-consistent and asymptotically normal as n goes to infinity and m is fixed; this has been proved by B. Rønn and I. Skovgaard in an ...
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Mean Empirical Likelihood
... Empirical likelihood methods are widely used in different settings to construct the confidence regions for parameters which satisfy the moment ...empirical likelihood ratio confidence regions may have poor ...
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Likelihood and Estimation
... These equations express the fact that the true values maximise the expected likelihoods,. which seem to be the only link between true values and likelihood in small samples[r] ...
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On the estimation of marginal cost
... the mean values from the actual data ...the estimation procedure ...of marginal cost must be able to approximate the true marginal cost even though total cost is clustered in two ...
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Two Sharp Inequalities for Power Mean, Geometric Mean, and Harmonic Mean
... ab and Ha, b 2 ab/a b denote the geometric mean and harmonic mean of a and b, respectively. Copyright q 2009 Y.-M. Chu and W.-F. Xia. This is an open access article distributed under the Creative ...
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