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Predictive Inference (predictive + inference)
Selected AbstractsNONPARAMETRIC BOOTSTRAP PROCEDURES FOR PREDICTIVE INFERENCE BASED ON RECURSIVE ESTIMATION SCHEMES,INTERNATIONAL ECONOMIC REVIEW, Issue 1 2007Valentina Corradi We introduce block bootstrap techniques that are (first order) valid in recursive estimation frameworks. Thereafter, we present two examples where predictive accuracy tests are made operational using our new bootstrap procedures. In one application, we outline a consistent test for out-of-sample nonlinear Granger causality, and in the other we outline a test for selecting among multiple alternative forecasting models, all of which are possibly misspecified. In a Monte Carlo investigation, we compare the finite sample properties of our block bootstrap procedures with the parametric bootstrap due to Kilian (Journal of Applied Econometrics 14 (1999), 491,510), within the context of encompassing and predictive accuracy tests. In the empirical illustration, it is found that unemployment has nonlinear marginal predictive content for inflation. [source] Non-parametric Predictive Inference for Age Replacement with a Renewal ArgumentQUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 3 2004P. Coolen-Schrijner Abstract We consider an age replacement problem with cost function based on the renewal reward theorem. However, instead of assuming a known probability distribution for the lifetimes, we apply Hill's assumption for predicting probabilities for the lifetime of a future item. Lower and upper bounds for the survival function of a future item are used, resulting in upper and lower cost functions. Minimizing these upper and lower cost functions to obtain the optimal age replacement times is simplified due to the special form of these functions. To discuss some features of our approach, we first study the consequences of using equally spaced percentiles from a known distribution instead of observed data. Secondly, we report on a simulation study where the lifetimes are simulated from known distributions, so that the optimal replacement times corresponding to our approach can be compared with the theoretical optimal replacement times. Copyright © 2004 John Wiley & Sons, Ltd. [source] Model uncertainty in cross-country growth regressionsJOURNAL OF APPLIED ECONOMETRICS, Issue 5 2001Carmen Fernández We investigate the issue of model uncertainty in cross-country growth regressions using Bayesian Model Averaging (BMA). We find that the posterior probability is spread widely among many models, suggesting the superiority of BMA over choosing any single model. Out-of-sample predictive results support this claim. In contrast to Levine and Renelt (1992), our results broadly support the more ,optimistic' conclusion of Sala-i-Martin (1997b), namely that some variables are important regressors for explaining cross-country growth patterns. However, care should be taken in the methodology employed. The approach proposed here is firmly grounded in statistical theory and immediately leads to posterior and predictive inference. Copyright © 2001 John Wiley & Sons, Ltd. [source] Bootstrap predictive inference for ARIMA processesJOURNAL OF TIME SERIES ANALYSIS, Issue 4 2004Lorenzo Pascual Abstract., In this study, we propose a new bootstrap strategy to obtain prediction intervals for autoregressive integrated moving-average processes. Its main advantage over other bootstrap methods previously proposed for autoregressive integrated processes is that variability due to parameter estimation can be incorporated into prediction intervals without requiring the backward representation of the process. Consequently, the procedure is very flexible and can be extended to processes even if their backward representation is not available. Furthermore, its implementation is very simple. The asymptotic properties of the bootstrap prediction densities are obtained. Extensive finite-sample Monte Carlo experiments are carried out to compare the performance of the proposed strategy vs. alternative procedures. The behaviour of our proposal equals or outperforms the alternatives in most of the cases. Furthermore, our bootstrap strategy is also applied for the first time to obtain the prediction density of processes with moving-average components. [source] Sentential and discourse context effects: adults who are learning to read compared with skilled readersJOURNAL OF RESEARCH IN READING, Issue 4 2007Katherine S. Binder In a series of three experiments, we examined how sentential and discourse contexts were used by adults who are learning to read compared with skilled adult readers. In Experiment 1, participants read sentence contexts that were either congruent, incongruent or neutral with respect to a target word they had to name. Both skilled and less skilled adults benefited from a congruent context, and were not disadvantaged by an incongruent context. Contrary to research conducted on children learning to read, skill level of the adult reader did not interact with context. Experiments 2 and 3 tested readers' ability to make predictive inferences. Again, all readers, regardless of skill level, provided evidence that they were making predictive inferences. This finding is inconsistent with research that has examined individual differences in college readers. [source] | ||||||||||