Apparent rates of dissolved gaseous mercury (DGM) concentration changes in a southern reservoir lake (Cane Creek Lake, Cookeville, Tennessee) were investigated using the DGM data collected in a 12-month study from June 2003 to May 2004. The monthly mean apparent DGM production rates rose from January (3.2 pg L(-1)/h), peaked in the summer months (June-August: 8.9, 8.0, 8.6 pg L(-1)/h), and fell...

SEASONAL cycles have long been analysed to study economic trends, but only within the past two decades has seasonal analysis been applied to congenital malformations. Since McKeown and Record (1951) carefully studied large numbers of anencephalic stillbirths and found a seasonal pattern of a winter excess and a summer trough, a steady output of articles dealing with the seasonality of malformat...

The literature has been notably less definitive in distinguishing between finite sample studies of seasonal stationarity than in seasonal unit root tests. Although the use of seasonal stationarity and unit root tests is advised to determine correctly the most appropriate form of the trend in a seasonal time series, such a use is rarely noted in the relevant studies on this topic. Recently, the ...

abstract one of the most variability of atmospheric parameter is precipitation, which changes seasonally. it is important to understand exact characteristic of rainfall seasonal variable. therefore, it is avoidable to study rainfall season in hamedan province, because hameden is one of the important centers of agriculture in iran. in this research, the seasonal variability of rainfall is consid...

This paper considers simultaneous modelling of seasonality, slowly changing unconditional variance and conditional heteroskedasticity in high-frequency nancial returns. A new approach, called a seasonal SEMIGARCH model, is proposed to perform this by introducing multiplicative seasonal and trend components into the GARCH model. A data-driven semiparametric algorithm is developed for estimating ...

Amaximization of the expected entropy of the predictive distribution interpretation of Akaike's minimum AIC procedure is exploited for the modeling and prediction of time series with trend and seasonal mean value functions and stationary covariances. The AIC criterion best one-step-ahead and best twelvestep-ahead prediction models are different. They exhibit the relative optimality properties f...

Data mining techniques are frequently used to extract the disease related factors from the huge datasets. Data mining is the task of discovering formerly unknown, appropriate patterns and relationships in huge datasets. Generally, each data mining task differs in the type of knowledge it extracts and the kind of data demonstration it uses to convey the discovered information. Forecasting is a p...