predictive distributions
CAS: Obtaining Predictive Distributions for Reserves Which Incorporate Expert Opinion
... It is also important that easy-to-use software is now available that allows us to implement the Bayesian models for loss reserving. While it is straightforward to define a Bayesian model, it is not always so easy to find ...
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Technical note: Combining quantile forecasts and predictive distributions of streamflows
... Abstract. The enhanced availability of many different hydro-meteorological modelling and forecasting systems raises the issue of how to optimally combine this great deal of information. Especially the usage of ...
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CAS: Bootstrap Estimation of the Predictive Distributions of Reserves Using Paid and Incurred Claims
... prediction distributions of reserves produced by the Mu- nich chain ladder (MCL) ...bootstrap distributions, this paper addresses the appli- cation of bootstrapping methods to dependent data, with the ...
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CAS: Estimating Predictive Distributions for Loss Reserve Models
... the predictive dis- tribution of future paid losses for an individ- ual ...prior distributions used in this method will be “derived” by an analysis of loss triangles for other ...prior distributions) ...
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Bootstrap Estimation of the Predictive Distributions of Reserves using Paid and Incurred Claims
... sampling distributions for statistical quantities of interest by generating pseudo samples, which are obtained by randomly drawing, with replacement, from observed ...
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Bootstrap Estimation of the Predictive Distributions of Reserves Using Paid and Incurred Claims
... sampling distributions for statistical quantities of interest by generating pseudo samples, which are obtained by randomly drawing, with replacement, from observed ...
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A joint calibration model for combining predictive distributions
... In many research fields, as for example in probabilistic weather forecasting, valuable predictive information about a future random phenomenon may come from several, pos- sibly heterogeneous, sources. Forecast ...
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Confounding and missing data in cost-effectiveness analysis: comparing different methods
... applying predictive margins in the frequentist inference and predictive distributions in the Bayesian inference to produce adjusted means of cost and effectiveness, and their ...negative ...
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Modelling Uncertainty in Collaborative Document Quality Assessment
... obtain predictive dis- tributions, we use RFs (Breiman, 2001), which are ensembles of decision trees (regression trees in our ...obtain predictive distributions, we as- sume that the individual tree ...
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Event and model dependent rainfall adjustments to improve discharge predictions
... Abstract Most conceptual rainfall–runoff models use as input spatially averaged rainfall fields which are typically associated with significant errors that affect the model outcome. In this study, it is hypothesized that ...
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Distribution of future location vector and residual sum of squares for multivariate location-scale model with spherically contoured errors
... The multivariate location-scale model with a family of spherically contoured errors is considered for both realized and future responses. The predictive distributions of the future location vector (FLV) and ...
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Pirfenidone for Treating Idiopathic Pulmonary Fibrosis: An Evidence Review Group Perspective of a NICE Single Technology Appraisal
... The main changes within the ERG’s preferred base-case were: • use of treatment effects estimated from the NMA from the CODA samples of the predictive distributions, using data up to 72 w[r] ...
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On the optimality of hedge fund investment strategies: a Bayesian skew t distribution model
... mean, predictive skewness and predictive covariance are obtained using expressions in equation (8) ...the predictive mean is equal to the posterior mean, and the predictive variance and ...
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Loss Distributions
... This paper is intended as a guide to statistical inference for loss distributions. There are three basic approaches to deriving the loss distribution in an insurance risk model: empirical, analytical, and moment ...
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On Bayesian nonparametric modelling of two correlated distributions
... two distributions (since the weights are now the same rather than just correlated). This sharing of information can be particularly useful in cases of few observations from one or both distributions. On the ...
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Characterizations of multinomial distributions based on conditional distributions
... In Section 3 a characterization of the joint multinomial of two identically distributed random vectors based on one conditional multinomial... distribution is given.[r] ...
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Selection, Training and Career Development of Naval Officers : A Long-Term Follow-Up Using Multivariate Techniques
... Standard 175 5 Distributions 182 6 Distribution 186 7 Associations 193 8 Predictive 196 9 Principal Training Component and Career 202 10 Principal Component 205 11 Component and Factor 2[r] ...
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Think Bayes: Bayesian Statistics Made Simple
... The premise of this book, and the other books in the Think X series, is that if you know how to program, you can use that skill to learn other topics. Most books on Bayesian statistics use mathematical notation and ...
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Spatial Distribution of Cabbage Root Maggot Delia radicum and Clubroot Plasmodiophora brassicae in Winter Oilseed Rape Crops in the Czech Republic
... cases. Distributions of CRM and clubroot symptom- atic plants were either significantly spatially dissociated or not associated in ...brassicae. Distributions of CRM and hypocotyl thickness levels were ...
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Computational Simulations of Similar Probabilistic Distributions to the Binomial and Poisson Distributions
... SMp(k;n,p) distributions. Also, this obtains the probabilistic distributions for a random discrete variable X with maximum probability in x=µ or x≈µ, and equal to zero in x ≥ Xmax, where µ is the Poisson ...
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