Extreme temperature of several stations in Malaysia is modelled by fitting the monthly maximum to the Generalized Extreme Value (GEV) distribution. The Mann-Kendall (MK) test suggests a non-stationary model. Two models are considered for stations with trend and the Likelihood Ratio test is used to determine the best-fitting model. Results show that half of the stations favour a model which is linear for the location parameters. The return level is the level of events (maximum temperature) which is expected to be exceeded once, on average, in a given number of years, is obtained
AbstractExtreme weather events can have severe consequences for the population and the environment. ...
When the extreme data were obtained from several sites in a region, spatial extreme analysis is alwa...
Max-stable processes are a common choice for modelling spatial extreme data as they arise naturally ...
Climate change is considered to be one of the biggest crisis which affects human life and nature. Th...
The issues on global warming have become very popular and been discussed both locally and internatio...
Statistical models of rainfall have been applied in the understanding of the rainfall past trends, i...
Flash floods are known as one of the common natural disasters that cost over billions of Ringgit Mal...
In this paper, temperature extremes are forecast by employing the block maxima method of the General...
With the current concern over climate change, the descriptions on how temperature series changed ove...
The purpose of this study is to compare the Generalized Extreme Value (GEV) parameter estimation by ...
Extreme temperature events bring significant effects on the environment and society. Consequently, i...
The Generalized Extreme Value (GEV) distribution is often used to describe the frequency of occurren...
Extreme value theory is a very well-known statistical analysis for modeling extreme data in environm...
Statistical distributions of annual extreme (AE) and partial duration (PD) for rainfall events are a...
The paper deals with the probabilistic estimates of extreme maximum rainfall (Annual basis) in the R...
AbstractExtreme weather events can have severe consequences for the population and the environment. ...
When the extreme data were obtained from several sites in a region, spatial extreme analysis is alwa...
Max-stable processes are a common choice for modelling spatial extreme data as they arise naturally ...
Climate change is considered to be one of the biggest crisis which affects human life and nature. Th...
The issues on global warming have become very popular and been discussed both locally and internatio...
Statistical models of rainfall have been applied in the understanding of the rainfall past trends, i...
Flash floods are known as one of the common natural disasters that cost over billions of Ringgit Mal...
In this paper, temperature extremes are forecast by employing the block maxima method of the General...
With the current concern over climate change, the descriptions on how temperature series changed ove...
The purpose of this study is to compare the Generalized Extreme Value (GEV) parameter estimation by ...
Extreme temperature events bring significant effects on the environment and society. Consequently, i...
The Generalized Extreme Value (GEV) distribution is often used to describe the frequency of occurren...
Extreme value theory is a very well-known statistical analysis for modeling extreme data in environm...
Statistical distributions of annual extreme (AE) and partial duration (PD) for rainfall events are a...
The paper deals with the probabilistic estimates of extreme maximum rainfall (Annual basis) in the R...
AbstractExtreme weather events can have severe consequences for the population and the environment. ...
When the extreme data were obtained from several sites in a region, spatial extreme analysis is alwa...
Max-stable processes are a common choice for modelling spatial extreme data as they arise naturally ...