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摘自:https://en.wikipedia.org/wiki/Gamma_distribution 1、描述 In probability theory and statistics, the gamma distribution is a two-parameter family of continuous probability distributions. The exponential distribution, Erlang distribution, and chi-squared distribution are special cases of the gamma distribution.There are three different parametrizations in common use: With a shape parameter k and a scale parameter θ (相当于均值).With a shape parameter α = k and an inverse scale parameter β = 1/θ, called a rate parameter(相当于均值的倒数).With a shape parameter k and a mean parameter μ = kθ = α/β. 上述所有参数都是正的实数。2、PDF和CDF的曲线和公式 scale参数即为:指数分布的均值。rate参数即为:指数分布的lambda。较容易混淆的参数,相当重要!!! The skewness of the gamma distribution only depends on its shape parameter, k, and it is equal to 实际生活相关:for example, the gamma distribution is frequently used to model waiting times. For instance, in life testing, the waiting time until death is a random variable that is frequently modeled with a gamma distribution. If k is a positive integer, then the distribution represents an Erlang distribution; i.e., the sum of k independent exponentially distributed random variables, each of which has a mean of θ. 3、伽马分布表示 A random variable X that is gamma-distributed with shape α and rate β is denoted: ,α = k
PDF: 形状α、尺度θ参数 形状α、速率β参数 其中,、、 或者 CDF:
表中的下不完全伽马函数可以进一步化简(具体化),一般在概率中较常用到: 化成1-上不完全伽马函数与伽马函数的关系式,进一步借助于下式: ,即可将CDF表示成累加形式,易于求概率和积分。
4、Summation 多个伽马分布的累加和 注意:尺度参数相同,仅形状参数累加 5、Scaling 尺度变换
注意:形状参数不变,仅尺度参数或速率参数被缩放 6、Logarithmic expectation and variance 对数的 digamma function 双伽玛函数:伽马分布的自然对数的导数。 In mathematics, the digamma function is defined as the logarithmic derivative of the gamma function:
也可以写成调和数的关系式: Hn是第n个调和数,γ是欧拉-马歇罗尼常数。
It is the first of the polygamma functions. 7、Related distributions and properties 相关的其他分布
补充概念: 调和数:the harmonic numbers are defined for positive integers n as
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