CRC Handbook of Tables for Order Statistics from Inverse Gaussian Distributions with Applications
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A01=N. Balakrishnan
A01=William Chen
advanced order statistics methods
ASN
Author_N. Balakrishnan
Author_William Chen
Category=PBT
Cumulative Distribution Function
Double Precision Format
econometric applications
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
extreme event prediction
fatigue analysis
Gaussian Quadrature
Gold Berger
graduate statistics textbook
Inverse Gaussian
Inverse Gaussian Model
Joint Density Functions
Life Test Experiment
Linear Unbiased Estimation
Linear Unbiased Estimators
Linear Unbiased Prediction
Linear Unbiased Predictor
Maximum Flood Levels
N. Balakrishnan
parameter
Passage Time Distributions
Quantile Quantile Plot
reliability engineering
shape
Shape Parameter
Simulated Percentage Points
Skew Symmetric Matrix
Standard Inverse Gaussian Distributions
Standard Normal Case
Standard Normal Density Function
Standardized Probability Density Function
statistical modeling
Susquehanna River
Wald Distributions
Product details
- ISBN 9780367448158
- Weight: 453g
- Dimensions: 178 x 254mm
- Publication Date: 13 Dec 2019
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Paperback
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First derived within the context of life-testing, inverse Gaussian distribution has become one of the most important and widely employed distributions, and is often used to model the lifetimes of components. It is also used as a model in many varied applications, including fatigue analysis, economic prediction analysis, and the analysis of extreme events such as rainfall and flood levels. The interesting features and properties of this distribution make it an important and realistic model in a variety of problems across numerous disciplines.
Because of the broad range of applications, this handbook will be useful not only to members of the statistical community but will also appeal to applied scientists, engineers, econometricians, and anyone who desires a thorough evaluation of this important topic.
Balakrishnan, N.; Chen, William
