在 R 中使用“extRemes”拟合广义极值 (GEV) 时出错？答案

【问题标题】：Error with fitting a Generalized Extreme Value (GEV) using `extRemes` in R?在 R 中使用“extRemes”拟合广义极值 (GEV) 时出错？
【发布时间】：2019-09-01 09:03:41
【问题描述】：

我有一些数据，我想在 R 中使用 extRemes 包拟合广义极值 (GEV) 分布。但是，出现错误：

library(extRemes)
Mydata = c(6,3,3,3,5,5,4,3,5,5,4,3,4,4,6,5,5,4,5,2,6,4,6,5,3,3,8,3,4,4,6,6,6,6,6,5,6,6,5,5)
fit_gev <- fevd(x=Mydata, method = "MLE", type="GEV", period.basis = "year")
summary(fit_gev)

Error in diag(cov.theta) : invalid 'nrow' value (too large or NA)
In addition: Warning message:
In diag(cov.theta) : NAs introduced by coercion

我想知道如何解决这个错误？感谢您的帮助。

【问题讨论】：

标签： r data-fitting

【解决方案1】：

您可以使用 EnvStats 包进行如下调整：

library(EnvStats)
# Data
Mydata =
c(6,3,3,3,5,5,4,3,5,5,4,3,4,4,6,5,5,4,5,2,6,4,6,5,3,3,8,3,4,4,6,6,6,6,6,5,6,6,5,5)    
# Generalized Extreme Value (EnvStats)
egevd(Mydata, method = "pwme")# (Method: probability-weighted moments)

Results of Distribution Parameter Estimation
--------------------------------------------

Assumed Distribution:            Generalized Extreme Value

Estimated Parameter(s):          location = 4.268896
                                 scale    = 1.314489
                                 shape    = 0.353434

Estimation Method:               Unbiased pwme

Data:                            Mydata

Sample Size:                     40

【讨论】：