• Journal of the Korean Statistical Society
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• v.27 no.1
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• pp.57-66
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• 1998

In the analysis of time series it is an important issue to determine whether a time series under study is stationary. For the test of the stationary of the time series the Dickey-Fuller (DF) type tests have been mainly used. In this paper, we consider the regular unit root tests and seasonal unit root tests based on the generalized Durbin-Watson (DW) statistics when the errors are independent. The limiting distributions of the proposed DW-type test statistics are the functionals of standard Brownian motions. We also obtain the finite distributions and powers of the DW-type test statistics and compare the performances with the DF-type tests. It is observed that the DW-type test statistics have good behaviors against the DF-type test statistics especially in the nonzero (seasonal) mean model.

• Journal of the Korean Statistical Society
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• v.26 no.3
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• pp.365-382
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• 1997

In this paper we study the behaviors of the generalized Durbin-Watson (DW) statistics when the nonstationary seasonal time series regression model is misspecified. It is observed that when the series is seasonally integrated the generalized DW statistic for the seasonal period order autocorrelation converges in probability to zero while teh generalized DW statistic for the first order autocorrelation has nondegenerate asymptotic distribution. When the series is regularly and seasonally integrated the generalized DW for the first order autocorrelation still converges in probability to zero.

• Communications for Statistical Applications and Methods
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• v.5 no.1
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• pp.55-67
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• 1998

Recent work by Shin and Sarkar (1996) examines model misspecification problems for nonstationary time series. Shin and Sarkar introduce a general regression model with integrated errors and one system of integrated regressors and discuss the limiting distributions of the OLS estimators and the usual OLS statistics such as $\hat{\sigma^2}$t, DW and $R^2$. We analyze three different model misspecification problems through a Monte Carlo study and investigate each model misspecification problem. Our Monte Carlo experiments show that DW and $R^2$ can be in general used as diagnostic tools to detect spurious regression, misspecification of nonstationary autoregressive and polynomial regression models.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.559-564
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• 2016

The Durbin-Watson (DW) test in regression model and the Ljung-Box (LB) test in ARMA (autoregressive moving average) model are typical examples of correlated error tests. The DW test is used for detecting autocorrelation of errors using the residuals from a regression analysis. The LB test is used for specifying the correct ARMA model using the first some sample autocorrelations based on the residuals of a tted ARMA model. In this article, simulations with four data generating processes have been carried out to evaluate their performances as correlated error tests. Our simulations show that the DW test is severely dependent on the assumed AR(1) model but isn't sensitive enough to reject the misspecified model and that the LB test reports lackluster performance in general.

• Atmosphere
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• v.33 no.1
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• pp.21-32
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• 2023

Characteristics of downslope windstorm (DW) has been examined mainly based on 1-min average wind and the other meteorological conditions in the Yeongdong region for 2000~2020. First, a classification procedure for the downslope windstorm is proposed using surface wind speed (greater than 99 percentile), 1-hour longevity of strong wind (SW), westerly wind direction, low humidity (less than 20 percentile), and leeside warming. The number of DW days satisfying the proposed criteria is 221 (2.9% of total days and 47.5% of SW days) while the number of SW days is 465 (6.1% of total days) for 2000~2020. The occurrences of both SW and DW shows distinctive annual variation with its peak in April. In addition, mean wind speed of DW days is 8.2 m s^-1 with its duration of 2 hr 30 min and relative humidity of 28% at Gangneung. An episode (7 May 2021) was selected by applying the proposed criteria to SW days of 2021. The sounding shows that the layer of wind speed greater than 25 m s^-1 was lowered down to 925 hPa at Gangneung (leeside) relative to 850 hPa at Hoengseong (Wonju), in the afternoon along with significant warming and drying. Froude numbers of Wonju and Gangneung for the DW events were increased 4 and 5 times greater than those of normal days, respectively. This kind of DW long-term statistics in the leeside of the mountains is thought to build a foundation of further understanding DW mechanism.

• Proceedings of the Safety Management and Science Conference
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• 2012.04a
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• pp.579-583
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• 2012

The Design of Experiment (DOE) is a most practical technique when establishing an optimal condition for production technology in Six Sigma innovation project. This research proposes the assessment of properties of error terms, such as normality, equal variance, unbiasedness and independence. The properties of six nonparametric ranking techniques for checking normality assumption are discussed as well as run test which is used to identify the randomness, and to check unbiased assumption. Furthermore, Durbin-Watson (DW) statistics and ARIMA (p,d,q) process are discussed to identify the serial correlation.

• Investigative Magnetic Resonance Imaging
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• v.21 no.3
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• pp.154-161
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• 2017

Purpose: To evaluate the diagnostic performance of diffusion-weighted steady-state free precession (DW-SSFP) in comparison to diffusion-weighted echo-planar imaging (DW-EPI) for differentiating the neoplastic and benign osteoporotic vertebral compression fractures. Materials and Methods: The subjects were 40 patients with recent vertebral compression fractures but no history of vertebroplasty, spine operation, or chemotherapy. They had received 3-Tesla (T) spine magnetic resonance imaging (MRI), including both DW-SSFP and DW-EPI sequences. The 40 patients included 20 with neoplastic vertebral fracture and 20 with benign osteoporotic vertebral fracture. In each fracture lesion, we obtained the signal intensity normalized by the signal intensity of normal bone marrow (SI norm) on DW-SSFP and the apparent diffusion coefficient (ADC) on DW-EPI. The correlation between the SI norm and the ADC in each lesion was analyzed using linear regression. The optimal cut-off values for the diagnosis of neoplastic fracture were determined in each sequence using Youden's J statistics and receiver operating characteristic curve analyses. Results: In the neoplastic fracture, the median SI norm on DW-SSFP was higher and the median ADC on DW-EPI was lower than the benign osteoporotic fracture (5.24 vs. 1.30, P = 0.032, and 0.86 vs. 1.48, P = 0.041, respectively). Inverse linear correlations were evident between SI norm and ADC in both neoplastic and benign osteoporotic fractures (r = -0.45 and -0.61, respectively). The optimal cut-off values for diagnosis of neoplastic fracture were SI norm of 3.0 in DW-SSFP with the sensitivity and specificity of 90.4% (95% confidence interval [CI]: 81.0-99.0) and 95.3% (95% CI: 90.0-100.0), respectively, and ADC of 1.3 in DW-EPI with the sensitivity and specificity of 90.5% (95% CI: 80.0-100.0) and 70.4% (95% CI: 60.0-80.0), respectively. Conclusion: In 3-T MRI, DW-SSFP has comparable sensitivity and specificity to DW-EPI in differentiating the neoplastic vertebral fracture from the benign osteoporotic vertebral fracture.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.95-107
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• 2008

Survey on the rural living indicators was the statistic approved from National Statistical Office and the survey executed by rural resources development institute. This study was used the raw data of survey on the rural living indicators in 2005. After editing procedure for raw data, we were studied 1,582 households which is acquired through elimination of case included nonresponses, and imputed a nonresponses of 15 item selected from 146 item. The imputation methods and efficiency of imputation for simulation was adapted differently from type of data. For continuous data, we imputed the nonresponses with mean imputation, regression imputation, adjusted grey-based k-NN imputation(DU, DW, WU, WW) and compared the results with RMSE. For categorical data, we imputed the nonresponses with mode method, probability imputation, conditional mode method, conditional probability method, hot-deck imputation, and compared the results with Accuracy. By the results, regression imputation and adjusted grey-based k-NN imputation appropriated for continuous data and hot-deck imputation appropriated for categorical data.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.161-174
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• 2007

In this paper, we propose a high performance database cluster system called HyperDB to process OLAP queries efficiently. HyperDB is a virtual database system running on top of internet-connected PCs; the PCs are used for their own purpose at ordinary times, but they are able to participate in the database cluster system at non-office hours. We propose fully logical replication technique and optimal parallel intra-query routing technique for extensibility and performance. Experiment for TPC-R benchmark shows significant performance upgrade compared with conventional approaches.