Conditional predictive ordinate
WebThis article introduces a novel use of the vine copula which captures dependence among multi-line claim triangles, especially when an insurance portfolio consists of more than two lines of business. First, we suggest a way to choose an optimal joint loss development model for multiple lines of business that considers marginal distribution, vine copula … WebMoreover, we develop an efficient Monte Carlo method for computing the conditional predictive ordinate statistics in the joint modeling setting. A simulation study is conducted to examine the empirical performance of the proposed criteria and the proposed methodology is further applied to a case study in mesothelioma. Supplementary materials ...
Conditional predictive ordinate
Did you know?
WebThe conditional predictive ordinate is a measure to detect surprising observations: small values indicate that the dth observation is surprising. Thus for a large value of IkdI … WebOct 19, 2024 · The package also offers several goodness of fit diagnostics such as QQ-plots, including a cross-validation criterion, the conditional predictive ordinate. The proposed methodology is illustrated on a classical ecological risk assessment method called the Species Sensitivity Distribution (SSD) problem, showcasing the benefits of the …
WebMar 14, 2024 · Hence, for each observation the conditional predictive ordinate is the posterior probability of observing that observation when the model is fit using all data for an observation at location s and time t. Large values indicate a better fit of the model to the data, while small values indicate a bad fit of the model. ... WebMay 20, 2024 · One specific PPC is the conditional predictive ordinate (CPO) which seeks to re-observe a datum y i given all other observed data, denoted y /i, This metric is equivalent to the posterior predictive …
WebJun 30, 2011 · Transition probabilities depend on the prior week's state, fixed demographic variables, and time-varying covariates. We adopt a Bayesian approach to model fitting, and use the conditional predictive ordinate statistic to demonstrate that the zero-inflated Poisson hidden Markov model outperforms other models for longitudinal count data. WebLater it was used to evaluate the predictive power of the model, and the ROC curve was derived based on the confusion matrix. The two main indicators in the ROC curve areReal rate和False positive rate, The benefits of this choice are also explained above. The abscissa is the false positive rate (FPR) and the ordinate is the true rate (TPR).
WebThe model is implemented in WinBUGS. I want to use CPO (Conditional Predictive Ordinate), but to be able to do that I need firstly to calculate PPO (Posterior Predictive Ordinate). I have know ...
WebDec 11, 2024 · The Conditional predictive ordinate values are significantly smaller (order of magnitude smaller) than the others, so the observed values would be considered surprising concerning the Bayesian log-normal model because the sum of the observations associated with failure flags is equal to zero in the HF data-set. The plots include a 95% ... editing message in discordWebJan 1, 2016 · Conditional predictive ordinate. The conditional predictive ordinate (CPO) statistics introduced by [9] is a popular and useful model assessment tool based … editing meshes using softwareWebThe conditional predictive ordinate (CPO) is a Bayesian diagnostic which detects surprising observations. It has been used in a variety of situations such as univariate … editing mesh in solidworks