one of the most important hydrological time series task is to determine if there is any trend in the data and how to achieve stationarity when there is nonstationarity behavior in data. detecting trend and stationarity in hydrological time series may help us to understand the possible links between hydrological processes and global climate changes. in this study yearly, monthly and daily stream...

In this paper we propose a new set of multivariate stochastic models that capture time varying seasonality within the vector innovations structural time series (VISTS) framework. These models encapsulate exponential smoothing methods in a multivariate setting. The models considered are the local level, local trend and damped trend VISTS models with an additive multivariate seasonal component. W...

BACKGROUND Time trends and seasonal patterns have been observed in nurse staffing and nursing-sensitive patient outcomes in recent years. It is unknown whether these changes were associated. METHODS Quarterly unit-level nursing data in 2004-2012 were extracted from the National Database of Nursing Quality Indicators® (NDNQI®). Units were divided into groups based on patterns of missing data. ...

introduction: air temperature as an important climatic factor can influence variability and distribution of other climatic parameters. therefore, tracking the changes in air temperature is a popular procedure in climate change studies.. according to the national academy in the last decade, global temperature has raised 0.4 to 0.8⁰c. instrumental records show that, with the exception of 1998, th...

One of the most important hydrological time series task is to determine if there is any trend in the data and how to achieve stationarity when there is nonstationarity behavior in data. Detecting trend and stationarity in hydrological time series may help us to understand the possible links between hydrological processes and global climate changes. In this study yearly, monthly and daily stream...

The physical mechanism underlying ENSO’s phase locking to the seasonal cycle is examined in three parameter regimes: the fast-SST limit, the fast-wave limit, and the mixed SST–wave dynamics regime. The seasonal cycle is imposed on simple ordinary differential equation models for each physical regime either as a seasonal ocean– atmosphere coupling strength obtained from the model of Zebiak and C...

This paper presents statistical investigations regarding the value of the trend concept and calendar effects for prediction of stock returns. The examined data covers 207 stocks on the Swedish stock market for the time period 1987-1996. The results show a very weak trend behavior. The massive better part of returns falls into a region, where it is very difficult to claim any correlation between...

BACKGROUND Domesticated horses adapt to environmental conditions through seasonal fluctuations in their metabolic rate. The seasonal change of metabolic rates of domesticated horses in pastures is documented. However, there are few investigations on seasonal body weight change of domesticated horses housed in stables, which are provided constant energy intake throughout the year. Both seasonal ...

The ARIMA-model-based methodology of programs TRAMO and SEATS for seasonal adjustment and trend-cycle estimation was applied to the exports, imports, and balance of trade Japanese series in Maravall (2002). The programs were used in an automatic mode, and the results analyzed. The present paper contains an extension of the work. First, some improvements in the automatic modelling procedure are ...

[1] Many long-term records of climate variables have missing data or have had changes in their times of observation. Here we present a technique to analyze such inhomogeneous records. We assume that the underlying climatic processes are nonstationary, where the observations contain a long-term trend superimposed on periodic shorter time seasonal and diurnal cycles. The seasonal and diurnal vari...