查看“︁Gamma distribution”︁的源代码

==英語==
{{wikipedia|lang=en}}

===名詞===
{{en-noun}}

# {{lb|en|probability theory|statistics}} {{w|伽玛分布}}
#* {{quote-book|en|year=1988|author=A. Clifford Cohen; Betty Jones Whitten|title=Parameter Estimation in Reliability and Life Span Models|publisher=w:Marcel Dekker|pageurl=https://books.google.com.au/books?id=cMIBqiz2xEEC&pg=PA93&dq=%22gamma+distribution%22%7C%22gamma+distributions%22&hl=en&sa=X&ved=0ahUKEwjysse325nWAhVG5GMKHSzPCioQ6AEIrwEwHA#v=onepage&q=%22gamma%20distribution%22%7C%22gamma%20distributions%22&f=false|page=93
|passage=The '''gamma distribution''' is positively skewed and along with the Weibull, lognormal, and inverse Gaussian (IG) distributions is also available as a model in reliability and life-span studies.}}
#* '''1999''' [1977, Wiley], Jean Dickinson Gibbons, Ingram Olkin, Milton Sobel, ''Selecting and Ordering Populations: A New Statistical Methodology'', {{w|工業與應用數學學會|SIAM}}, Republished unabridged and corrected, [https://books.google.com.au/books?id=Y4AvUzc9RqUC&pg=PA328&dq=%22gamma+distribution%22%7C%22gamma+distributions%22&hl=en&sa=X&ved=0ahUKEwjysse325nWAhVG5GMKHSzPCioQ6AEI3wEwJg#v=onepage&q=%22gamma%20distribution%22%7C%22gamma%20distributions%22&f=false page 328],
#*: {{quote|en|The ranking and selection problems in this chapter apply to populations that follow the '''gamma distribution'''. The '''gamma distribution''' model is used widely in many fields of applications, particularly in engineering and the social and physical sciences.|t=本章中的排序和选择问题适用于服从'''伽马分布'''的群体。伽马分布模型广泛应用于许多实用领域，特别是在工程、社会和物理科学领域。}}
#* {{quote-book|en|year=2005|author=M. T. Todinov|title=Reliability and Risk Models: Setting Reliability Requirements|publisher=Wiley|pageurl=https://books.google.com.au/books?id=Umw7q_vNRO4C&pg=PA36&dq=%22gamma+distribution%22%7C%22gamma+distributions%22&hl=en&sa=X&ved=0ahUKEwjysse325nWAhVG5GMKHSzPCioQ6AEIPTAF#v=onepage&q=%22gamma%20distribution%22%7C%22gamma%20distributions%22&f=false|page=36
|passage=The negative exponential distribution is a special case of the '''gamma distribution''' in which <math>k = 1</math>. Another important special case of a '''gamma distribution''' with parameters <math>k</math> and <math>\theta = 2</math> is the [[chi-square distribution|χ² distribution]] <math>G(k, 2)</math> with <math>n = 2k</math> degrees of freedom.{{...}}'''Gamma distributions''' have an additivity property: the sum of two random variables following '''gamma distributions''' <math>G(k_1,\theta)</math> and <math>G(k_2,\theta)</math> is a random variable following a '''gamma distribution''' <math>G(k_1 + k_2,\theta)</math> with parameters <math>k_1 + k_2</math> and <math>\theta</math>{{...}}.}}