scholarly journals Estimation of Change-point and Post-change Parameters after Adaptive Sequential CUSUM Test in an Exponential Family

2016 ◽  
Vol 5 (5) ◽  
pp. 43 ◽  
Author(s):  
Yanhong Wu
Keyword(s):  
Change Point ◽  
Exponential Family ◽  
River Flow ◽  
Temperature Data ◽  
Nile River ◽  
Data Sets ◽  
Cusum Test ◽  
First Order ◽  
Average Global Temperature ◽  
Cusum Procedure

In this paper, we consider an adaptive sequential CUSUM procedure in an exponential family where the change-point and post-change parameters are estimated adaptively. It is shown that the adaptive CUSUM procedure is efficient at the first order. The conditional biases of the estimation for the change-point and post-change parameter are studied. Comparison with the classical CUSUM procedure in the normal case is made. Nile river flow and average global temperature data sets are used for demonstration.

scholarly journals An Alternate Generalized Odd Generalized Exponential Family with Applications to Premium Data

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2064
Author(s):  
Sadaf Khan ◽  
Oluwafemi Samson Balogun ◽  
Muhammad Hussain Tahir ◽  
Waleed Almutiry ◽  
Amani Abdullah Alahmadi
Keyword(s):  
Exponential Family ◽  
Simulation Analysis ◽  
Structural Characteristics ◽  
Stochastic Ordering ◽  
Quantile Function ◽  
Risk Theory ◽  
Data Sets ◽  
Exponential Distributions ◽  
New Family ◽  
Lehmann Alternative

In this article, we use Lehmann alternative-II to extend the odd generalized exponential family. The uniqueness of this family lies in the fact that this transformation has resulted in a multitude of inverted distribution families with important applications in actuarial field. We can characterize the density of the new family as a linear combination of generalised exponential distributions, which is useful for studying some of the family’s properties. Among the structural characteristics of this family that are being identified are explicit expressions for numerous types of moments, the quantile function, stress-strength reliability, generating function, Rényi entropy, stochastic ordering, and order statistics. The maximum likelihood methodology is often used to compute the new family’s parameters. To confirm that our results are converging with reduced mean square error and biases, we perform a simulation analysis of one of the special model, namely OGE2-Fréchet. Furthermore, its application using two actuarial data sets is achieved, favoring its superiority over other competitive models, especially in risk theory.

scholarly journals Model cascade from meteorological drivers to river flood hazard: flood-cascade v1.0

2021 ◽  
Vol 14 (8) ◽  
pp. 4865-4890
Author(s):  
Peter Uhe ◽  
Daniel Mitchell ◽  
Paul D. Bates ◽  
Nans Addor ◽  
Jeff Neal ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
River Flow ◽  
Climate Model ◽  
Climate Modeling ◽  
Flood Hazard ◽  
Spatial Scales ◽  
Computational Cost ◽  
Data Sets ◽  
Flood Inundation

Abstract. Riverine flood hazard is the consequence of meteorological drivers, primarily precipitation, hydrological processes and the interaction of floodwaters with the floodplain landscape. Modeling this can be particularly challenging because of the multiple steps and differing spatial scales involved in the varying processes. As the climate modeling community increases their focus on the risks associated with climate change, it is important to translate the meteorological drivers into relevant hazard estimates. This is especially important for the climate attribution and climate projection communities. Current climate change assessments of flood risk typically neglect key processes, and instead of explicitly modeling flood inundation, they commonly use precipitation or river flow as proxies for flood hazard. This is due to the complexity and uncertainties of model cascades and the computational cost of flood inundation modeling. Here, we lay out a clear methodology for taking meteorological drivers, e.g., from observations or climate models, through to high-resolution (∼90 m) river flooding (fluvial) hazards. Thus, this framework is designed to be an accessible, computationally efficient tool using freely available data to enable greater uptake of this type of modeling. The meteorological inputs (precipitation and air temperature) are transformed through a series of modeling steps to yield, in turn, surface runoff, river flow, and flood inundation. We explore uncertainties at different modeling steps. The flood inundation estimates can then be related to impacts felt at community and household levels to determine exposure and risks from flood events. The approach uses global data sets and thus can be applied anywhere in the world, but we use the Brahmaputra River in Bangladesh as a case study in order to demonstrate the necessary steps in our hazard framework. This framework is designed to be driven by meteorology from observational data sets or climate model output. In this study, only observations are used to drive the models, so climate changes are not assessed. However, by comparing current and future simulated climates, this framework can also be used to assess impacts of climate change.

scholarly journals Anomalies and trends of high river flow under temperate climatic conditions in north-eastern Romania

2020 ◽  
Author(s):  
Ionuț Minea ◽  
Oana Elena Chelariu
Keyword(s):  
Water Resource Management ◽  
River Flow ◽  
Climatic Conditions ◽  
High Flow ◽  
Data Sets ◽  
Pi Index ◽  
Starting Point ◽  
North Eastern ◽  
Management Plans ◽  
High River Flow

Abstract Regional water resource management plans include various scenarios related to the anomalies and trends of hydro-climatic parameters. Two methods are used for the identification of the anomalies and trends associated with high flow (annual and seasonal) of the rivers in Eastern Romania, namely the quantile perturbation method (QPM) and the partial trend method (PMT). These methods were selected due to the fact that they are suitable for data sets which do not rely on restrictive statistical assumption as common parametric and nonparametric trend tests do. For six of the nine stations analyzed, the decreasing trend in high extremes for annual high flow based on the PTM is the same as the annual trend obtained with the QPM. Using the PI index (associated with PTM) for the estimation of trend intensity, values between −2.280 and −9.015 m3/s were calculated for the decreasing trend of the annual high flow and between +1,633 m3/s (in autumn) and −9.940 m3/s (in summer) for the seasonal high flow. The results obtained on the anomalies and trends of high river flow may represent a starting point in the analysis of the evolution of water resources and their effective management.

scholarly journals Climate change impact on river flow extremes in the Upper Blue Nile River basin

2018 ◽  
Vol 10 (4) ◽  
pp. 759-781 ◽  
Author(s):  
Hadush K. Meresa ◽  
Mulusew T. Gatachew
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Change Impact ◽  
River Flow ◽  
Nile River ◽  
Hydrological Models ◽  
Hydrological Extremes ◽  
Dry Spell ◽  
Change Impact ◽  
Blue Nile River Basin

Abstract This paper aims to study climate change impact on the hydrological extremes and projected precipitation extremes in far future (2071–2100) period in the Upper Blue Nile River basin (UBNRB). The changes in precipitation extremes were derived from the most recent AFROCORDEX climate data base projection scenarios compared to the reference period (1971–2000). The climate change impacts on the hydrological extremes were evaluated using three conceptual hydrological models: GR4 J, HBV, and HMETS; and two objective functions: NSE and LogNSE. These hydrological models are calibrated and validated in the periods 1971–2000 and 2001–2010, respectively. The results indicate that the wet/dry spell will significantly decrease/increase due to climate change in some sites of the region, while in others, there is increase/decrease in wet/dry spell but not significantly, respectively. The extreme river flow will be less attenuated and more variable in terms of magnitude, and more irregular in terms of seasonal occurrence than at present. Low flows are projected to increase most prominently for lowland sites, due to the combined effects of projected decreases in Belg and Bega precipitation, and projected increases in evapotranspiration that will reduce residual soil moisture in Bega and Belg seasons.

Parametric modelling of turbulence

1990 ◽  
Vol 332 (1627) ◽  
pp. 439-455 ◽  
Keyword(s):  
Long Range ◽  
Three Dimensional ◽  
Large Data ◽  
Theoretical Work ◽  
Long Range Dependence ◽  
Dependence Structure ◽  
Data Sets ◽  
Parametric Modelling ◽  
First Order ◽  
Log Linear

Some steps are taken towards a parametric statistical model for the velocity and velocity derivative fields in stationary turbulence, building on the background of existing theoretical and empirical knowledge of such fields. While the ultimate goal is a model for the three-dimensional velocity components, and hence for the corresponding velocity derivatives, we concentrate here on the stream wise velocity component. Discrete and continuous time stochastic processes of the first-order autoregressive type and with one-dimensional marginals having log-linear tails are constructed and compared with two large data-sets. It turns out that a first-order autoregression that fits the local correlation structure well is not capable of describing the correlations over longer ranges. A good fit locally as well as at longer ranges is achieved by using a process that is the sum of two independent autoregressions. We study this type of model in some detail. We also consider a model derived from the above-mentioned autoregressions and with dependence structure on the borderline to long-range dependence. This model is obtained by means of a general method for construction of processes with long-range dependence. Some suggestions for future empirical and theoretical work are given.

scholarly journals Optimal Algorithms for Computing Average Temperatures

2019 ◽  
Vol 5 (1) ◽  
pp. 34-44
Author(s):  
S. Foucart ◽  
M. Hielsberg ◽  
G. L. Mullendore ◽  
G. Petrova ◽  
P. Wojtaszczyk
Keyword(s):  
Optimal Algorithm ◽  
A Priori ◽  
Global Temperature ◽  
Data Sets ◽  
Average Temperature ◽  
Generic Models ◽  
Average Global Temperature ◽  
A Priori Bound ◽  
Average Precipitation

AbstractA numerical algorithm is presented for computing average global temperature (or other quantities of interest such as average precipitation) from measurements taken at speci_ed locations and times. The algorithm is proven to be in a certain sense optimal. The analysis of the optimal algorithm provides a sharp a priori bound on the error between the computed value and the true average global temperature. This a priori bound involves a computable compatibility constant which assesses the quality of the measurements for the chosen model. The optimal algorithm is constructed by solving a convex minimization problem and involves a set of functions selected a priori in relation to the model. It is shown that the solution promotes sparsity and hence utilizes a smaller number of well-chosen data sites than those provided. The algorithm is then applied to canonical data sets and mathematically generic models for the computation of average temperature and average precipitation over given regions and given time intervals. A comparison is provided between the proposed algorithms and existing methods.

Multivariate analysis for medium- and long-range forecasting of Nile River flow to mitigate drought and flood risks

2021 ◽  
Author(s):  
Hossam M. Ahmed ◽  
Ayman G. Awadallah ◽  
Alaa El-Din M. El-Zawahry ◽  
Khaled H. Hamed
Keyword(s):  
Multivariate Analysis ◽  
Long Range ◽  
River Flow ◽  
Nile River ◽  
Flood Risks ◽  
Drought And Flood

scholarly journals THE NILE LITTORAL CELL AND MAN'S IMPACT ON THE COASTAL ZONE OF THE SOUTHEASTERN MEDITERRANEAN

1984 ◽  
Vol 1 (19) ◽  
pp. 109 ◽  
Author(s):  
Douglas L. Inman ◽  
Scott A. Jenkins
Keyword(s):  
Coastal Waters ◽  
Coastal Erosion ◽  
Large Scale ◽  
River Flow ◽  
Nile Delta ◽  
Mediterranean Coast ◽  
Nile River ◽  
Sediment Source ◽  
Littoral Cell ◽  
The Mediterranean

Man's intervention with coastal processes takes many forms. However, the most serious large scale, long term coastal erosion results from the interception by dams of rivers supplying sediment to the coast. This loss of sediment may have catastrophic effects along coasts where streams discharge directly into coastal waters. The Nile littoral cell is an impressive example of the effect of dams on coastal erosion. The Nile littoral cell is located in the southeastern Mediterranean Sea and extends 700 km from Alexandria, Egypt in the south to Akko, Israel in the north. The sediment load from the Nile River was deposited along the submerged portion of the delta, where it was sorted and transported to the east by the prevailing waves and by currents of the counterclockwise east Mediterranean gyre that commonly flows at about 50 cm sec over the delta. Prior to 1964, the turbid plume of the flood waters of the Nile River could be traced along the Mediterranean coast for over 700 km to the shores of Lebanon. Fine silt and clay sized material were carried easterly and into deeper water, while sand is carried easterly along the shelf and shore as far as Haifa Bay. Until 1964, the major sediment source of the littoral cell was the Nile River. Construction of the High Aswan Dam, which began filling in 1964, has resulted in a near absence of Nile River flow into the Mediterranean and a corresponding complete loss of the Nile River as a source of nutrients to coastal waters, and as an active sediment source for the delta and the coastline of the Nile littoral cell. As a result, the Nile Delta is now subject to severe erosion in a number of localities.

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