BACKGROUND Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. METHODS Monthly mean raw mortality (at hospital discharge) time series, 1995-2009, at the individual Intensive ...

Tests for unit roots in univariate time series with level shifts are proposed and investigated The level shift is assumed to occur at a known time It may be a simple one time shift which can be captured by a dummy variable or it may have a more general form which can be modeled by some general nonlinear transition function There may also be more than one shift point and there may be other deter...

Extracting and forecasting the volatility of financial markets is an important empirical problem. Time series of realized volatility or other volatility proxies, such as squared returns, display long range dependence. Exponential smoothing (ES) is a very popular and successful forecasting and signal extraction scheme, but it can be suboptimal for long memory time series. This paper discusses po...

Smooth Transition Exponential Smoothing (STES) is a popular exponential smoothing method for volatility forecasting; whereby the success of STES model lies in choice transition variable. In this paper, three realized variance (RV), daily, weekly and monthly RV were used as variables methods to evaluate performance intraday data. While daily squared return noisy series, residual employed proxy a...

The purpose of the article is to analyze main performance indicators agricultural entrepreneurship functioning and development assess prospects for its development. following methods are used in research: analysis synthesis, analytical generalizations, graphic – development; statistical, extrapolation, constructive-computational, mathematical modelling, time series decomposition forecasting ent...

In this paper, the Shiryaev-Roberts (SR) procedure is examined and compared with the change point CUSUM (CPC) procedure for monitoring the dispersion of a normal process. It will be shown that the SR chart performs better than the CPC chart for the pre-specified dispersion shift. In practice, when the magnitude of a future dispersion shift is unknown, it is always desired to design a control ch...

In this thesis, we consider the clustering of time series data; specifically, time series that can be modeled in the state space framework. Of primary focus is the pairwise discrepancy between two state space time series. The state space model can be formulated in terms of two equations: the state equation, based on a latent process, and the observation equation. Because the unobserved state pr...