• Communications for Statistical Applications and Methods
• /
• v.12 no.3
• /
• pp.797-805
• /
• 2005

Multivariate unit root tests for the VAR(p) model have been commonly used in time series analysis. Several unit root tests were developed and recently Shin(2004) suggested a cointegration test based on weighted symmetric estimator. In this paper, we suggest a multivariate unit root test statistic based on the weighted symmetric estimator. Using a small simulation study, we compare the powers of the new test statistic with the statistics suggested in Shin(2004) and Fuller(1996).

• Journal of the Korean Statistical Society
• /
• v.24 no.2
• /
• pp.481-493
• /
• 1995

An ARIMA signal observed with measurement error is shown to have another ARIMA representation with nonlinear restrictions on parameters. For this model, the restricted Newton-Raphson estimator(RNRE) of the unit root is shown to have the same limiting distribution as the ordinary least squares estimator of the unit root in an AR(1) model tabulated by Dickey and Fuller (1979). The RNRE of parameters of the ARIMA(p,1,k) process and unit root tests base on the RNRE are developed.

• Communications for Statistical Applications and Methods
• /
• v.11 no.2
• /
• pp.323-327
• /
• 2004

In this paper, we investigate the limiting distribution of the Ljung-Box test statistic in the unit root AR models with ARCH errors. We show that the limiting distribution is approximately chi-square distribution with the degrees of freedom only depending on the number of autocorrelation lags appearing in the test. Some simulation results are provided for illustration.

• Journal of the Korean Statistical Society
• /
• v.27 no.2
• /
• pp.165-187
• /
• 1998

Shin and Sarkar (1993, 1994) studied the problem of testing for a unit root in an AR(p) signal observed with MA(q) noise when the MA parameters are known. In this paper we consider the case when the MA parameters are unknown and to be estimated. Test statistics are defined using unit root parameter estimates based on three different estimation methods of Hannan and Rissanen (1982), Kohn (1979) and Shin and Sarkar (1995). An AR(p) process contaminated by MA(q) noise is a .estricted ARMA model, for which Shin and Sarkar (1995) derived an easy-to-compute Newton- Raphson estimator The two-stage estimation p.ocedu.e of Hannan and Rissanen (1982) is used to compute initial parameter estimates in implementing the iterative estimation methods of both Shin and Sarkar (1995) and Kohn (1979). In a simulation study we compare the relative performance of these unit root tests with respect to both size and power for p=q=1.

• Journal of the Korean Statistical Society
• /
• v.36 no.1
• /
• pp.149-156
• /
• 2007

This study suggests a new method for testing seasonal unit roots in a momentum threshold autoregressive (MTAR) process. This sign test is robust against heteroscedastic or heavy tailed errors and is invariant to monotone data transformation. The proposed test is a seasonal extension of the sign test of Park and Shin (2006). In the case of partial seasonal unit root in an MTAR model, a Monte-Carlo study shows that the proposed test has better power than the seasonal sign test developed for AR model.

• Proceedings of the Korean Statistical Society Conference
• /
• 2003.05a
• /
• pp.183-189
• /
• 2003

A momentum threshold autoregressive (MTAR) model, a nonlinear autoregressive model, is analyzed in a Bayesian framework. Parameter estimation in the presence of missing data is done by using Markov chain Monte Carlo methods. We also propose simple Bayesian test procedures for asymmetry and unit roots. The proposed method is applied to a set of Korea unemployment rate data and reveals evidence for asymmetry and a unit root.

• Journal of the Korean Statistical Society
• /
• v.26 no.3
• /
• pp.397-405
• /
• 1997

Recently maximum likelihood estimators using unconditional likelihood function are used for testing unit roots. When one wants to use this method the determinant term of initial values in the multivariate unconditional likelihood function produces a complicated function of the elements in the coefficient matrix and variance matrix. In this paper an approximation of the determinant term is calculated and based on this aproximation an approximated unconditional likelihood function is calculated. The approximated unconditional maximum likelihood estimators can be used to test for unit roots. When multivariate process has one unit root the limiting distribution obtained by this method and the limiting distribution using exact unconditional likelihood function are the same.

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

• The Korean Journal of Applied Statistics
• /
• v.24 no.1
• /
• pp.11-23
• /
• 2011

Robust unit root tests are developed for dynamic panels consisting of TAR processes. The test statistics are all based on diverse combinations of individual t-type tests for significance of TAR coefficients. Limiting null distributions are established. A Monte-Carlo experiment compares the proposed tests. The tests are applied to a panel data set of Canadian unemployment rates which show asymmetric features as well as having outliers.

• The Journal of Korean Academy of Prosthodontics
• /
• v.31 no.3
• /
• pp.303-316
• /
• 1993

The purpose of this study was to analysis the stress distribution induced by three unit PFM bridges and various cantilever bridges replacing maxillary latersal incisor. The simplified two-dimensional photoelastic models used for this study was contructed in the folio- wing way. CR/R ratio was designed to be 1 : 1, 1 : 1.25 and 1 : 1.5. The pontics of cantilever bridge supported by maxillary canines consisted of wrap-around type, rest-extension type, and simple type. 3-unit PFM bridge was constructed with traditional method. 1kg vertical static load was applied on the center of the incisal edge of the pontic. The stress pattern was examined and recorded by photography. The results obtained were as follows ; 1. The magnitude of stress on the abutment root apex area of a traditional 3-unit bridge was the lowest. 2. The model of cantilevered pontic with a rest showed the relatively well distributed stress around the abutment tooth. The model with simple pontic generated the greatest stress concentration in the supporting structure of the abutment tooth. 3. As the height of bone level reduced, the rotational and vertical force increased around the abutment tooth. 4. The stress concentration of the 3-unit bridges occured on the root apex and stress concentration of the cantilever briage occured on the root apex and cervix area, 5. In the case of the cantilever bridge, stress concentrated distally on the root apex area of the abutment tooth and additional stress was observed mesially on the upper part of the root. Especially in the case of the simple pontic, was phenomenon was more apparent than the others. 6. Force applied to cantilevered pontic was transmitted to the adjacent central incisor through the contact surface. Stress was markedly observed on the mesial cervix area in the case of simple pontic and on the root apex area in the case of wrap-around type and rest-extension type.