问题描述
这张来自Wikipedia的图片有一个很好的例子，说明了我理想情况下希望产生的那种功能:
This picture from Wikipedia has a nice example of the sort of functions I'd ideally like to generate:
现在，我使用的是Irwin-Hall分布，它或多或少是高斯分布的多项式近似值...基本上，您使用统一随机数生成器并将其迭代x次，然后取平均值.迭代次数越多，就越像高斯分布.
Right now I'm using the Irwin-Hall Distribution, which is more or less a polynomial approximation of the Gaussian distribution...basically, you use uniform random number generator and iterate it x times, and take the average. The more iterations, the more like a Gaussian Distribution it is.
非常好；但是我希望能够有一个可以改变均值的位置.例如，假设我想要一个介于0到10之间的数字，但 around 7.例如，平均值(如果我多次重复此函数)将变成7，但实际范围是0-10.
It's pretty nice; however I'd like to be able to have one where I can vary the mean. For example, let's say I wanted a number between the range 0 and 10, but around 7. Like, the mean (if I repeated this function multiple times) would turn out to be 7, but the actual range is 0-10.
我应该查一下吗，还是应该使用标准的高斯分布来做一些奇特的数学运算?
Is there one I should look up, or should I work on doing some fancy maths with standard Gaussian distributions?
推荐答案
我发现您的问题有矛盾之处.一方面，您希望其性质为对称的正态分布；另一方面，您希望将范围非对称地分布为平均值.
I see a contradiction in your question. From one side you want normal distribution which is symmetrical by it's nature, from other side you want the range asymmetrically disposed to mean value.
我怀疑您应该尝试看看其他分布密度函数，例如钟形曲线，但不对称.类似于日志分发或测试版发布.
I suspect you should try to look at other distributions density functions of which are like bell curve but asymmetrical. Like log distribution or beta distribution.
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