Tests of fit for the Gumbel distribution: EDF-based tests against entropy-based tests

2019 ◽  
Vol 47 (10) ◽  
pp. 1885-1900
Author(s):  
Hadi Alizadeh Noughabi ◽  
Jalil Jarrahiferiz
Keyword(s):  
Gumbel Distribution ◽  
Tests Of Fit

Variable Control Charts for Gumbel Distribution Based on Percentiles

2018 ◽  
Vol 9 (12) ◽  
pp. 1890-1897
Author(s):  
K. Rosaiah ◽  
B. Srinivasa Rao ◽  
J. Pratapa Reddy ◽  
C. Chinnamamba
Keyword(s):  
Control Charts ◽  
Gumbel Distribution ◽  
Variable Control

Design Inflow Intensity and Design Inflow Profiles for Storm Sewers

1984 ◽  
Vol 16 (8-9) ◽  
pp. 207-218 ◽  
Author(s):  
Frans H M van de Ven
Keyword(s):  
Return Period ◽  
Gumbel Distribution ◽  
Extreme Value Distribution ◽  
Data Series ◽  
Design Discharge ◽  
Common Location ◽  
Housing Area ◽  
Parking Lot ◽  
Box Cox Transformation ◽  
Frequency Curves

Twelve year records of rainfall and of sewer inflow data in a housing area and in a parking lot in Lelystad were available. These data series contained 5-minute depths of rainfall and sewer inflow. Depth-duration-frequency curves were calculated from the monthly extremes, using Box-Cox transformation and a Gumbel distribution. The differences between the curves for rainfall and for inflow are explained by inertia and rainfall losses. These differences are the reason to use inflow as a sewer design parameter. Forthe choice of the design discharge (or inflow) intensity the curves are not well suited. Storage-design,discharge-frequency curves proved to be better interprétable. The selected design discharge is 4 or 5 m3/s/km2. For non-steady flow calculations in sewer systems an inflow profile has to be provided. The prof ileshould be peaked. The most common location of the peak lies between 20 and 50% of the event duration. The return period of the profile has to be known. A bivariate extreme value distribution is used to estimate this return period. From these distributions synthetic inflow profiles could be calculated.

scholarly journals Modeling Best Practice Life Expectancy Using Gumbel Autoregressive Models

Risks ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 51
Author(s):  
Anthony Medford
Keyword(s):  
Time Series ◽  
Life Expectancy ◽  
Extreme Value Theory ◽  
Autoregressive Model ◽  
Best Practice ◽  
Gumbel Distribution ◽  
Value Theory ◽  
Model Diagnostics ◽  
Temporal Dependence ◽  
Simulation Results

Best practice life expectancy has recently been modeled using extreme value theory. In this paper we present the Gumbel autoregressive model of order one—Gumbel AR(1)—as an option for modeling best practice life expectancy. This class of model represents a neat and coherent framework for modeling time series extremes. The Gumbel distribution accounts for the extreme nature of best practice life expectancy, while the AR structure accounts for the temporal dependence in the time series. Model diagnostics and simulation results indicate that these models present a viable alternative to Gaussian AR(1) models when dealing with time series of extremes and merit further exploration.

scholarly journals Application of Frequency Analysis on Peak River Discharge toward the Cumulative Floatable Litter Load at Log Boom Sungai Batu

2019 ◽  
Vol 266 ◽  
pp. 02002
Author(s):  
Nur Khaliesah Abdul Malik ◽  
Nor Rohaizah Jamil ◽  
Latifah Abd Manaf ◽  
Mohd Hafiz Rosli ◽  
Zulfa Hanan Ash’aari ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
River Discharge ◽  
Linear Regression Analysis ◽  
Gumbel Distribution ◽  
Environmental Issues ◽  
Decision Making Process ◽  
Rapid Urbanization ◽  
Distribution Method ◽  
Period 2

The accumulation of floatable litter in the river is mainly influenced by the increasing number of human population, rapid urbanization and development which indirectly lead to the changes of hydrological processes in river discharge, decreasing the water quality and aesthetical value of the river. The main objective of this paper is to determine the cumulative floatable litter load captured at the log boom during the extreme events by using the Gumbel distribution method for frequency analysis in river discharge of Sungai Batu. The annual maximum river discharge for a period of 35 years (1982 to 2016) was used in Gumbel distribution method to obtain the discharge for different return period (2, 5, 10, 25, 50, 100, and 200). The result shows that the estimated discharge (103.17 m³/s) can estimate the cumulative floatable litter load (53267.27 kg/day) at 50 years return period. The R2 value obtained from non – linear regression analysis is 0.9986 indicate that Gumbel distribution is suitable to predict the expected discharge of the river. This study is very crucial for the related agencies in highlighting this environmental issues for their future references which can be used as a guidelines during the decision making process in making better improvement.

Estimating Housing Mortality with Standard Loss Curves

1986 ◽  
Vol 18 (11) ◽  
pp. 1521-1530 ◽  
Author(s):  
M E Gleeson
Keyword(s):  
Survival Data ◽  
Statistical Models ◽  
Life Tables ◽  
Time To Failure ◽  
Truncated Data ◽  
Mobile Homes ◽  
Analytical Work ◽  
Tests Of Fit

Tests of fit using one set of data on mobile homes and another on conventional housing indicate that standard loss curves, such as the Pearl-Reed and Weibull curves, can be used to approximate housing survivorship functions. This finding opens up the possibility of analytical work using standard curves and the application of time-to-failure statistical models that are based on such curves. Tests of fit of standard curves to the two housing survivorship functions using truncated data are also encouraging, suggesting means of estimating housing mortality and computing life tables with incomplete cohort survival data.

ACCEPTANCE SAMPLING PLANS FOR PERCENTILES OF GUMBEL DISTRIBUTION

2021 ◽  
Vol 62 (2) ◽  
pp. 113-130
Author(s):  
B. Srinivas Rao ◽  
C. Chinnamamba ◽  
K. Rosaiah
Keyword(s):  
Gumbel Distribution ◽  
Acceptance Sampling ◽  
Sampling Plans ◽  
Acceptance Sampling Plans

An Extreme Value Model for U.S. Hail Size

2017 ◽  
Vol 145 (11) ◽  
pp. 4501-4519 ◽  
Author(s):  
John T. Allen ◽  
Michael K. Tippett ◽  
Yasir Kaheil ◽  
Adam H. Sobel ◽  
Chiara Lepore ◽  
...  
Keyword(s):  
Gumbel Distribution ◽  
The United States ◽  
Value Theory ◽  
Extreme Value ◽  
Extreme Value Distributions ◽  
The Past ◽  
Return Levels ◽  
Data Limitations ◽  
Extreme Value Model ◽  
Value Model

The spatial distribution of return intervals for U.S. hail size is explored within the framework of extreme value theory using observations from the period 1979–2013. The center of the continent has experienced hail in excess of 5 in. (127 mm) during the past 30 yr, whereas hail in excess of 1 in. (25 mm) is more common in other regions, including the West Coast. Observed hail sizes show heavy quantization toward fixed-diameter reference objects and are influenced by spatial and temporal biases similar to those noted for hail occurrence. Recorded hail diameters have been growing in recent decades because of improved reporting. These data limitations motivate exploration of extreme value distributions to represent the return periods for various hail diameters. The parameters of a Gumbel distribution are fit to dithered observed annual maxima on a national 1° × 1° grid at locations with sufficient records. Gridded and kernel-smoothed return sizes and quantiles up to the 200-yr return period are determined for the fitted Gumbel distribution. These results are used to illustrate return levels for hail greater than a given size for at least one location within each 1° × 1° grid box for the United States.

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