matlab的极大似然估计问题

我也在学习。正在找例子呢。

[...] = mle(data,'pdf',pdf,'cdf',cdf,'start',start,...) returns MLEs for the parameters of the distribution defined by the probability density and cumulative distribution functions pdf and cdf. pdf and cdf are function handles created using the @ sign. They accept as inputs a vector data and one or more individual distribution parameters, and return vectors of probability density values and cumulative probability values, respectively. If the 'censoring' name/value pair is not present, you can omit the 'cdf' ame/value pair. mle computes the estimates by numerically maximizing the distribution's log-likelihood, and start is a vector containing initial values for the parameters.

结合传统优化方法中的惩罚函数法,描述了遗传算法和大型工程计算软件MATLAB 中遗传优化工具箱的使用方法。应用表明,将...如何由样本估计三参数威布尔分布的参数是工程中的一个重要问题,常用方法是极大似然法和图估计法进行参数估计

不懂