Time series analysis and modelling represent a large study field, implying the approach from the perspective of the time and frequency, with applications in different domains. Modelling hydro-meteorological time series is difficult due to the characteristics of these series, as long range dependence, spatial dependence, the correlation with other series. Continuous spatial data plays an important role in planning, risk assessment and decision making in environmental management. In this context, in this book we present various statistical tests and modelling techniques used for time series analysis, as well as applications to hydro-meteorological series from Dobrogea, a region situated in the south-eastern part of Romania, less studied till ...
In recent years the ecological conditions in areas of important wetlands have markedly changed. One ...
The objective of this thesis is to develop and refine statistical methods which can be used for solv...
The class of ARFIMA models offers a flexible tool to describe long memory time series and it has a s...
The main intent of this paper is to present a review on the application of time series analysis tech...
The analysis and management of Hydrology time series is used for the development of models that allo...
The principle of stationarity plays an important role in time series analysis. A key assumption in c...
Current climate conditions raise questions about how climate change should affect the hydrological r...
Time series models are often used in hydrology and meteorology studies to model streamflows series in...
Stochastic models in conventional time series analysis are mainly based on three key assumptions: st...
The generation of hydrologic time series is the starting point of the systematic analysis for the st...
Diploma thesis extends my Bachelor´s thesis, which was about methods of time distribution of precipi...
The prediction of a time series using the dynamical systems approach requires the knowledge of three...
Three aspects of stochastic analysis and modeling of hydrologic time series are investigated in this...
The program Menyanthes combines a variety of functions for managing, editing, visualizing, analyzing...
A large number of hydrological phenomena may be regarded as realizations of space-time random functi...
In recent years the ecological conditions in areas of important wetlands have markedly changed. One ...
The objective of this thesis is to develop and refine statistical methods which can be used for solv...
The class of ARFIMA models offers a flexible tool to describe long memory time series and it has a s...
The main intent of this paper is to present a review on the application of time series analysis tech...
The analysis and management of Hydrology time series is used for the development of models that allo...
The principle of stationarity plays an important role in time series analysis. A key assumption in c...
Current climate conditions raise questions about how climate change should affect the hydrological r...
Time series models are often used in hydrology and meteorology studies to model streamflows series in...
Stochastic models in conventional time series analysis are mainly based on three key assumptions: st...
The generation of hydrologic time series is the starting point of the systematic analysis for the st...
Diploma thesis extends my Bachelor´s thesis, which was about methods of time distribution of precipi...
The prediction of a time series using the dynamical systems approach requires the knowledge of three...
Three aspects of stochastic analysis and modeling of hydrologic time series are investigated in this...
The program Menyanthes combines a variety of functions for managing, editing, visualizing, analyzing...
A large number of hydrological phenomena may be regarded as realizations of space-time random functi...
In recent years the ecological conditions in areas of important wetlands have markedly changed. One ...
The objective of this thesis is to develop and refine statistical methods which can be used for solv...
The class of ARFIMA models offers a flexible tool to describe long memory time series and it has a s...