Andere Kunden interessierten sich auch für
![Analytical Study of Air Traffic Using ARFIMA Time Series Models]( "Analytical Study of Air Traffic Using ARFIMA Time Series Models")
Analytical Study of Air Traffic Using ARFIMA Time Series Models45,99 €![Construction of Advanced Machine Learning Models for Air Traffic]( "Construction of Advanced Machine Learning Models for Air Traffic")
Construction of Advanced Machine Learning Models for Air Traffic45,99 €![Statistical Analysis of Extremes]( "Statistical Analysis of Extremes")
Statistical Analysis of Extremes47,99 €![Statistical Methods for Linking Health Effects to Air Pollution]( "Statistical Methods for Linking Health Effects to Air Pollution")
Statistical Methods for Linking Health Effects to Air Pollution52,99 €![Stochastic Models of Air Pollutant Concentration]( "Stochastic Models of Air Pollutant Concentration")
Stochastic Models of Air Pollutant Concentration39,99 €![Introduction to Empirical Processes and Semiparametric Inference]( "Introduction to Empirical Processes and Semiparametric Inference")
Introduction to Empirical Processes and Semiparametric Inference151,99 €![Resampling Methods for Dependent Data]( "Resampling Methods for Dependent Data")
Resampling Methods for Dependent Data177,99 €
The main aim of this work is to apply Generalized Extreme Value distribution under Linear normalization (GEVL) and Generalized Pareto Distribution under Linear normalization (GPDL) to modeling air pollutant in El Sharkia governorate in Egypt. Also, to solve the problem of the choice peak over threshold in the case of GPDL and the validity of bootstrap method in the case of GEVL modeling. We suggest the sub-sample bootstrap method to convert any data to block data to use it for GEVL modeling. Moreover, we introduced the Generalized Pareto Distribution under Power normalization (GPDP), which enables us to suggest an efficient method for modeling extreme value under power normalization. We present statistical inference about the upper tail distribution for (GPDP). We also compare between the modeling under linear normalization and under power normalization. Finally, in the last chapter of this book the inconsistent and weak consistency of bootstrapping central and intermediate orderstatistics for an appropriate choice o re-sample size are investigated.