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Liu-Qin Yang Edward L. Levine Mark A. Smith Dan Ispas Michael E. Rossi 《Human Resource Management Review》2008,18(4):311
The purpose of this study was to examine if the non-linear terms in polynomial regression analysis (PRA) explain substantial amounts of variance in assumed outcomes over and above the linear terms. This meta-analysis reviewed a total of 30 studies from 25 articles on person–environment (P-E) fit in which PRA was used. We found that none of the 30 studies did rigorous cross-validation for PRA. In addition, the overall population R2 change attributable to the non-linear terms (PE, P2 and E2) in PRA was only .008. However, the P-E interaction term may be more important in some situations than in others, based on the data gathered here. Specifically, the non-linear terms in PRA added to the variance explained by the linear terms (P and E) when studies examined assumed outcome variables like contextual performance or job attitudes as opposed to task performance. In summary, PRA could potentially be effective in investigating P-E fit and other human resource management-related phenomena when it is used in appropriate scenarios. 相似文献
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Fast and frugal forecasting 总被引:3,自引:2,他引:1
Simple statistical forecasting rules, which are usually simplifications of classical models, have been shown to make better predictions than more complex rules, especially when the future values of a criterion are highly uncertain. In this article, we provide evidence that some of the fast and frugal heuristics that people use intuitively are able to make forecasts that are as good as or better than those of knowledge-intensive procedures. We draw from research on the adaptive toolbox and ecological rationality to demonstrate the power of using intuitive heuristics for forecasting in various domains including sport, business, and crime. 相似文献
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《管理科学学报(英文)》2019,4(1):1-11
Macroeconomic forecasting in China is essential for the government to take proper policy decisions on government expenditure and money supply, among other matters. The existing literature on forecasting Chinas macroeconomic variables is unclear on the crucial issue of how to choose an optimal window to estimate parameters with rolling out-of-sample forecasts. This study fills this gap in forecasting economic growth and inflation in China, by using the rolling weighted least squares (WLS) with the practically feasible cross-validation (CV) procedure of Hong et al. (2018) to choose an optimal estimation window. We undertake an empirical analysis of monthly data on up to 30 candidate indicators (mainly asset prices) for a span of 17 years (2000–2017). It is documented that the forecasting performance of rolling estimation is sensitive to the selection of rolling windows. The empirical analysis shows that the rolling WLS with the CV-based rolling window outperforms other rolling methods on univariate regressions in most cases. One possible explanation for this is that these macroeconomic variables often suffer from structural changes due to changes in institutional reforms, policies, crises, and other factors. Furthermore, we find that, in most cases, asset prices are key variables for forecasting macroeconomic variables, especially output growth rate. 相似文献
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《International Journal of Forecasting》2020,36(2):695-712
Demand forecasting is and has been for years a topic of great interest in the electricity sector, being the temperature one of its major drivers. Indeed, one of the challenges when modelling the load is to choose the right weather station, or set of stations, for a given load time series. However, only a few research papers have been devoted to this topic. This paper reviews the most relevant methods that were applied during the Global Energy Forecasting Competition of 2014 (GEFCom2014) and presents a new approach to weather station selection, based on Genetic Algorithms (GA), which allows finding the best set of stations for any demand forecasting model, and outperforms the results of existing methods. Furthermore its performance has also been tested using GEFCom2012 data, providing significant error improvements. Finally, the possibility of combining the weather stations selected by the proposed GA using the BFGS algorithm is briefly tested, providing promising results. 相似文献
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In commercial banking, various statistical models for corporate credit rating have been theoretically promoted and applied
to bank-specific credit portfolios. In this paper, we empirically compare and test the performance of a wide range of parametric
and nonparametric credit rating model approaches in a statistically coherent way, based on a ‘real-world’ data set. We repetitively
(k times) split a large sample of industrial firms’ default data into disjoint training and validation subsamples. For all model types, we estimate k out-of-sample discriminatory power measures, allowing us to compare the models coherently. We observe that more complex and
nonparametric approaches, such as random forest, neural networks, and generalized additive models, perform best in-sample.
However, comparing k out-of-sample cross-validation results, these models overfit and lose some of their predictive power. Rather than improving
discriminatory power, we perceive their major contribution to be their usefulness as diagnostic tools for the selection of
rating factors and the development of simpler, parametric models.
相似文献
Stefan DenzlerEmail: |
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In this paper we consider the problem of testing for equality of two density or two conditional density functions defined over mixed discrete and continuous variables. We smooth both the discrete and continuous variables, with the smoothing parameters chosen via least-squares cross-validation. The test statistics are shown to have (asymptotic) normal null distributions. However, we advocate the use of bootstrap methods in order to better approximate their null distribution in finite-sample settings and we provide asymptotic validity of the proposed bootstrap method. Simulations show that the proposed tests have better power than both conventional frequency-based tests and smoothing tests based on ad hoc smoothing parameter selection, while a demonstrative empirical application to the joint distribution of earnings and educational attainment underscores the utility of the proposed approach in mixed data settings. 相似文献
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