Bayesian estimates of equation system parameters, An application of integration by Monte Carlo

By T. Kloek, H. V. Dijk. 1976

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Citations in the corpus

Online Continual Learning on Class Incremental Blurry Task Configuration with Anytime Inference (2021, methodology): “Inspired by works on sample importance (Kloek & Van Dijk, 1978; LeCun et al., 1990; Chang et al., 2017; Katharopoulos & Fleuret, 2018; Csiba & Richt´arik, 2018), we propose a novel sampling strategy speciﬁc for CL that removes samples from the memory based on sample-wise importance as following…”
Importance sampling: a review (2010, unknown): “ĉv2(λ; λ′) = 1 m ∑m j=1 [g(x)/qλ′ (x(j))]2 [qλ(x|)/qλ′ (x(j))] [ 1 m ∑m j=1 g(x)/qλ′(x) ]2 − 1 (7)”
Likelihood INference for Discretely Observed Non-linear Diffusions (2001, background): “Ž .sampling, see Kloek and van Dijk 1978 , Ripley 1987, pp. 122 123 , or Geweke Ž .”
Forecasting with Bayesian Vector Autoregression (2013, unknown): “Koop and Korobilis (2009) and DelNegro and Schorfheide (2011) provides complementary reviews of Bayesian VAR models, Koop and Korobilis (2009) with a focus on models that allows for time-varying parameters and stochastic volatility while DelNegro and Schorfheide (2011) has the broader remit of Bayes”
Bayesian Forecasting of Value at Risk and Expected Shortfall Using Adaptive Importance Sampling (2010, background): “…weights w(X̃) = p(X̃) q(X̃) with p(x) a kernel of the target density p∗(x) of X: p(x) ∝ p∗(x).5 4IS, see Hammersley and Handscomb (1964), has been introduced in Bayesian inference by Kloek and Van Dijk (1978) and is further developed by Van Dijk and Kloek (1980, 1984) and Geweke (1989).”
Asymptotic and Bayesian confidence intervals for sharpe-style weights (2000, background): “This is essentially what is done by Lobosco and DiBartolomeo (1997). However, if some of the “true” style weights * i β are on the boundary (i.”
Testing the assumptions behind importance sampling (2009, unknown): “Papers that carry out maximum likelihood analysis of SV models using importance sampling include Danielsson (1994), Shephard and Pitt (1997), Durbin and Koopman (1997), Sandmann and Koopman (1998), Durham and Gallant (2002), Durham (2003), Liesenfeld and Richard (2003), Brandt and Kang (2004), Durha”
BAYESIAN REFERENCE ANALYSIS OF COINTEGRATION (2005, methodology): “Another method that may be used to approximate the integral with respect tob in ~4+1! is importance sampling~Kloek and van Dijk, 1978; Geweke, 1989!+ In cases where the importance function well approximates the target integrand, importance sampling can be quite efficient as it produces independent…”