• Journal of the Korean Statistical Society
• /
• v.33 no.2
• /
• pp.149-157
• /
• 2004

The stationarity is one of the most important properties of a time series. We propose robust sign tests for seasonal autoregressive processes to determine whether or not a time series is stationary. The proposed tests are robust to the outliers and the heteroscedastic errors, and they have an exact binomial null distribution regardless of the period of seasonality and types of median adjustments. A Monte-Carlo simulation shows that the sign test is locally more powerful than the tests based on ordinary least squares estimator (OLSE) for heavy-tailed and/or heteroscedastic error distributions.

• Proceedings of the Korean Statistical Society Conference
• /
• 2002.11a
• /
• pp.279-285
• /
• 2002

In this paper we consider the problem of testing for structural changes in ARIMA models based on a cusum test. In particular, the proposed test procedure is applicable to testing for a change of the status of time series from stationarity to nonstationarity or vice versa. The idea is to transform the time series via differencing to make stationary time series. We propose a graphical method to identify the correct order of differencing.

• Journal of the Korean Professional Engineers Association
• /
• v.44 no.2
• /
• pp.23-28
• /
• 2011

The assumption that the spatiotemporal distribution of rainfall has stationarity for a long period is not realistic due to frequent unusual weather phenomena. Based on the understanding of the situation, this paper investigates the effects of it to hydraulic structures especially dams and deals measures for it.

• Communications for Statistical Applications and Methods
• /
• v.6 no.1
• /
• pp.267-274
• /
• 1999

We consider a doubly stochastically perturbed dynamical system {$X_n$} generated by $X_n\Gamma_n(X_{n-1})+W_n where \Gamma_n$ is a Markov chain of random functions and $W_n$ is i.i.d. random elements. Sufficient conditions for stationarity and geometric ergodicity of $X_n$ are obtained by considering asymptotic behaviours of the associated Markov chain. Ergodic theorem and functional central limit theorem are proved.

• Journal of applied mathematics & informatics
• /
• v.5 no.3
• /
• pp.785-796
• /
• 1998

In this paper we propose a model of HIv population through method of phases with non-Markovian evolution of immi-gration. The analysis leads to an explicit differnetial equations for the generating functions of the total population size. The detection process of antibodies (against the antigen of virus) is analysed and an explicit expression for the correlation functions are provided. A measure of bunching is also introduced for some particular choice of parameters.

• Communications for Statistical Applications and Methods
• /
• v.1 no.1
• /
• pp.149-156
• /
• 1994

For an r > 2 and a finite B, $E\mid max \;1\leq k\leq n \;\sum\limits_{j=m+1}^{m+k}X_j\mid^r\leq Bn^ {\frac{r}{2}}$ (all $n\geq 1$) is obtained for a negatively associated sequence $\{X_j \;:\; j\in N\}$. We also derive the maximal inequelity for a negatively associated sequence. Stationarity is not required.

• Proceedings of the Korean Statistical Society Conference
• /
• 2003.05a
• /
• pp.281-286
• /
• 2003

The stationarity is one of the most important properties of a time series. We propose robust sign tests for seasonal autoregressive process to determine whether or not a time series is stationary. The tests have an exact binomial null distribution and are robust to the outliers and the heteroscedastic errors. Monte-Carlo simulation shows that the sign test is locally more powerful than the OLSE-based tests for heavy-tailed and/or heteroscedastic error distributions.

• Communications for Statistical Applications and Methods
• /
• v.19 no.5
• /
• pp.639-646
• /
• 2012

The exponential continuous time GARCH(p,q) model for financial assets suggested by Haug and Czado (2007) is considered, where the log volatility process is driven by a general L$\acute{e}$vy process and the price process is then obtained by using the same L$\acute{e}$vy process as driving noise. Uniform ergodicity and ${\beta}$-mixing property of the log volatility process is obtained by adopting an extended generator and drift condition.

• Journal of the Korean Mathematical Society
• /
• v.32 no.2
• /
• pp.279-287
• /
• 1995

Let $F$ be a set of distributions on R with the topology of weak convergence, and let $A$ be the $\sigma$-field generated by the open sets. We denote by $F_1^\infty$ the space consisting of all infinite sequence $(F_1, F_2, \cdots), F_n \in F and R_1^\infty$ the space consisting of all infinite sequences $(x_1, x_2, \cdots)$ of real numbers. Take the $\sigma$-field $F_1^\infty$ to be the smallest $\sigma$-field of subsets of $F_1^\infty$ containing all finite-dimensional rectangles and take $B_1^\infty$ to be the Borel $\sigma$-field $R_1^\infty$.

• Communications for Statistical Applications and Methods
• /
• v.18 no.2
• /
• pp.229-236
• /
• 2011

A continuous time stochastic volatility model for financial assets suggested by Barndorff-Nielsen and Shephard (2001) is considered, where the volatility process is modelled as an Ornstein-Uhlenbeck type process driven by a general L$\'{e}$vy process and the price process is then obtained by using an independent Brownian motion as the driving noise. The uniform ergodicity of the volatility process and exponential ${\alpha}$-mixing properties of the log price processes of given continuous time stochastic volatility models are obtained.