再次求助，急～～～如何对广义帕累托分布进行参数估计 [推广有奖]

11楼

王菜林 发表于 2014-9-26 10:49:03

wenjc 发表于 2009-10-29 09:45
用matlab里的gpfit 可以做对了你的阈值是怎么确定下来的可以告诉下么我给你发了消息 qq讨论下吧

你好，请问gpfit（x）得到的两个数值代表的是形状参数和尺度参数吗？O(∩_∩)O谢谢

12楼

wenjc 发表于 2014-11-5 13:55:17

王菜林发表于 2014-9-26 10:47
你好，请问gpfit（x）得到的两个数值代表的是形状参数和尺度参数吗？O(∩_∩)O谢谢

gpfit
Generalized Pareto parameter estimates

Syntax

parmhat = gpfit(X)
[parmhat,parmci] = gpfit(X)
[parmhat,parmci] = gpfit(X,alpha)
[...] = gpfit(X,alpha,options)

Description

parmhat = gpfit(X) returns maximum likelihood estimates of the parameters for the two-parameter generalized Pareto (GP) distribution given the data in X. parmhat(1) is the tail index (shape) parameter, K and parmhat(2) is the scale parameter, sigma. gpfit does not fit a threshold (location) parameter.

[parmhat,parmci] = gpfit(X) returns 95% confidence intervals for the parameter estimates.

[parmhat,parmci] = gpfit(X,alpha) returns 100(1-alpha)% confidence intervals for the parameter estimates.

[...] = gpfit(X,alpha,options) specifies control parameters for the iterative algorithm used to compute ML estimates. This argument can be created by a call to statset. See statset('gpfit') for parameter names and default values.

Other functions for the generalized Pareto, such as gpcdf allow a threshold parameter, theta. However, gpfit does not estimate theta. It is assumed to be known, and subtracted from X before calling gpfit.

When K = 0 and theta = 0, the GP is equivalent to the exponential distribution. When K > 0 and theta = sigma/K, the GP is equivalent to the Pareto distribution. The mean of the GP is not finite when K ≥ 1, and the variance is not finite when K ≥ 1/2. When K ≥ 0, the GP has positive density for

X > theta, or, when K < 0, for

0≤ x−θσ ≤ −1k