bootstrappinginterval forecastingtime seriesThis paper examines small sample properties of alternative bias-corrected bootstrap prediction regions for the vector autoregressive (VAR) model. Bias-corrected bootstrap prediction regions are constructed by combining bias-correction of VAR parameter estimators with...
Bootstrapping Goodness-of-Fit Measures in Structural Equation Models Source: Sociological Methods & Research Structural Equations with Latent Variables Source: Unknown Repository Bootstrap‐corrected ADF test statistics in covariance structure analysis ...
the literature is very limited and cases study oriented. There are only three studies that have measured the efficiency of NISs in these countries together. Cai (2011) has studied the NISs of 22 countries including BRICS and G7. The findings of this study showed that BRICS’s NISs have low...
RIs were estimated using a bias-corrected bootstrapping approach. Electrocardiographic RIs were heart rate: 103 鈥 132 (beats/minute); P: 0.02 - 0.04, T: 0.03 - 0.04 waves durations (seconds); P: 0.13 - 0.23, R: 1.19 - 1.51, T: 0.20 - 0.27 waves amplitudes (mV...
Hyndman, Half-life estimation based on the bias corrected bootstrap: A highest density region approach, Computational Statistics and Data Analysis. 51 (7) (2007) 3418-3432.Half-Life Estimation based on the Bias-Corrected Bootstrap: A Highest Density Region Approach - Kim, Silvapulle, et al. ...
BootstrappingUnit rootThe parameter estimators of autoregressive (AR) models are biased in small samples, and these biases can adversely affect their forecast accuracy. The purpose of this paper is to evaluate the effect of bias-correction for AR parameter estimators on forecast accuracy. The bias...
BootstrappingIn efficiency studies, inputs and outputs are often noisy measures, especially when education data is used. This article complements the conditional efficiency model by correcting for bias within conditional draws, using themout ofnbootstrap procedure. With a unique panel dataset, we ...