我想对我拥有的一些数据点进行对数Pearson III。但是，每次尝试时，都会收到错误消息，但我实际上并不知道该怎么办。我也许应该补充一点，因为几天前我才使用R，所以我不是专家。
重要的代码部分，没有导入内容的部分等等是这样的：
pIIIpars<-list(shape=1, location=1, scale=1)
dPIII<-function(x, shape, location, scale) PearsonDS::dpearsonIII(x, shape=1, location=1, scale=1, params=pIIIpars, log=FALSE)
pPIII<-function(q, shape, location, scale) PearsonDS::ppearsonIII(q, shape=1, location=1, scale=1, params=pIIIpars, lower.tail = TRUE, log.p = FALSE)
qPIII<-function(p, shape, location, scale) PearsonDS::qpearsonIII(p, shape=1, location=1, scale=1, params=pIIIpars, lower.tail = TRUE, log.p = FALSE)
fitPIII<-fitdistrplus::fitdist(flowdata3$OEP, distr="PIII", method="mle", start=list("shape"=5000, "location"=5000, "scale"=5000))
summary(fitPIII)
plot(fitPIII)
我正在使用PearsonDS软件包定义Log Pearson III发行版，并使用fitdistrplus进行拟合。
我总是得到的错误消息是这样的：
[1] "Error in optim(par = vstart, fn = fnobj, fix.arg = fix.arg, obs = data, : \n function cannot be evaluated at initial parameters\n"
attr(,"class")
[1] "try-error"
attr(,"condition")
<simpleError in optim(par = vstart, fn = fnobj, fix.arg = fix.arg, obs = data, ddistnam = ddistname, hessian = TRUE, method = meth, lower = lower, upper = upper, ...): function cannot be evaluated at initial parameters>
Error in fitdistrplus::fitdist(flowdata3$OEP, distr = "PIII", method = "mle", :
the function mle failed to estimate the parameters,
with the error code 100
我确实不理解错误消息，只是；如果那不是传递初始值的正确方法，那是什么？
有人有主意吗？
干杯，
罗伯特
最佳答案
以下示例遵循Kite（2004）并与他的结果相符。
# Annual maximum discharge data for the St Mary River at Stillwater Nova Scotia (Kite, 2004)
# PIII fit to the logs of the discharges
StMary <- c(565,294,303,569,232,405,228,232,394,238,524,368,464,411,368,487,394,
337,385,351,518,365,515,280,289,255,334,456,479,334,394,348,428,337,
311,453,328,564,527,510,371,824,292,345,442,360,371,544,552,651,190,
202,405,583,725,232,974,456,289,348,564,479,303,603,514,377,318,342,
593,378,255,292)
LStMary <- log(StMary)
m <- mean(LStMary)
v <- var(LStMary)
s <- sd(LStMary)
g <- e1071::skewness(LStMary, type=1)
# Correct the sample skew for bias using the recommendation of
# Bobee, B. and R. Robitaille (1977). "The use of the Pearson Type 3 and Log Pearson Type 3 distributions revisited."
# Water Resources Reseach 13(2): 427-443, as used by Kite
n <- length(StMary)
g <- g*(sqrt(n*(n-1))/(n-2))*(1+8.5/n)
# We will use method of moment estimates as starting values for the MLE search
my.shape <- (2/g)^2
my.scale <- sqrt(v)/sqrt(my.shape)*sign(g) # modified as recommended by Carl Schwarz
my.location <- m-sqrt(v * my.shape)
my.param <- list(shape=my.shape, scale=my.scale, location=my.location)
dPIII<-function(x, shape, location, scale) PearsonDS::dpearsonIII(x, shape, location, scale, log=FALSE)
pPIII<-function(q, shape, location, scale) PearsonDS::ppearsonIII(q, shape, location, scale, lower.tail = TRUE, log.p = FALSE)
qPIII<-function(p, shape, location, scale) PearsonDS::qpearsonIII(p, shape, location, scale, lower.tail = TRUE, log.p = FALSE)
fitdistrplus::fitdist(LStMary, distr="PIII", method="mle", start=my.param)
另请注意，MLE估算值可能并不总是适用。参见风筝（2004，p119）。他引用了Matalas和Wallis（1973）的话，他们指出，如果样本偏斜很小，那么我就不可能找到解决方案。您可以在矩估计器的方法中看到这一点，因为随着g变为零，shape参数将爆炸。
Kite，G. W.（2004）水文学中的频率和风险分析。水资源出版物
Matalas，N。C.和J. R. Wallis（1973）。 “尤里卡！它符合Pearson Type 3发行版。”水资源研究9（2）：281-289。