R EVMIX 将 pdf 转换为统一边距
R EVMIX convert pdf to uniform marginals
我正在尝试将分布转换为伪均匀分布。使用 spd R 包,它很容易并且按预期工作。
library(spd)
x <- c(rnorm(100,-1,0.7),rnorm(100,3,1))
fit<-spdfit(x,upper=0.9,lower=0.1,tailfit="GPD", kernelfit="epanech")
uniformX = pspd(x,fit)
我想概括极值建模以包括阈值不确定性。所以我使用了 evmix 包。
library(evmix)
x <- c(rnorm(100,-1,0.7),rnorm(100,3,1))
fit = fgkg(x, phiul = FALSE, phiur = FALSE, std.err = FALSE)
pgkg(x,fit$lambda, fit$ul, fit$sigmaul, fit$xil, fit$phiul, fit$ur,
fit$sigmaur, fit$xir, fit$phiur)
我搞砸了。
请查看 pgkg 函数的帮助:
help(pgkg)
给出语法:
pgkg(q, kerncentres, lambda = NULL, ul = as.vector(quantile(kerncentres,
0.1)), sigmaul = sqrt(6 * var(kerncentres))/pi, xil = 0, phiul = TRUE,
ur = as.vector(quantile(kerncentres, 0.9)), sigmaur = sqrt(6 *
var(kerncentres))/pi, xir = 0, phiur = TRUE, bw = NULL,
kernel = "gaussian", lower.tail = TRUE)
您错过了内核中心(数据),内核密度估计器始终需要它。这是更正后的代码:
library(evmix)
x <- c(rnorm(100,-1,0.7),rnorm(100,3,1))
fit = fgkg(x, phiul = FALSE, phiur = FALSE, std.err = FALSE)
prob = pgkg(x, x, fit$lambda, fit$ul, fit$sigmaul, fit$xil, fit$phiul,
fit$ur, fit$sigmaur, fit$xir, fit$phiur)
hist(prob) % now uniform as expected
我正在尝试将分布转换为伪均匀分布。使用 spd R 包,它很容易并且按预期工作。
library(spd)
x <- c(rnorm(100,-1,0.7),rnorm(100,3,1))
fit<-spdfit(x,upper=0.9,lower=0.1,tailfit="GPD", kernelfit="epanech")
uniformX = pspd(x,fit)
我想概括极值建模以包括阈值不确定性。所以我使用了 evmix 包。
library(evmix)
x <- c(rnorm(100,-1,0.7),rnorm(100,3,1))
fit = fgkg(x, phiul = FALSE, phiur = FALSE, std.err = FALSE)
pgkg(x,fit$lambda, fit$ul, fit$sigmaul, fit$xil, fit$phiul, fit$ur,
fit$sigmaur, fit$xir, fit$phiur)
我搞砸了。
请查看 pgkg 函数的帮助:
help(pgkg)
给出语法:
pgkg(q, kerncentres, lambda = NULL, ul = as.vector(quantile(kerncentres,
0.1)), sigmaul = sqrt(6 * var(kerncentres))/pi, xil = 0, phiul = TRUE,
ur = as.vector(quantile(kerncentres, 0.9)), sigmaur = sqrt(6 *
var(kerncentres))/pi, xir = 0, phiur = TRUE, bw = NULL,
kernel = "gaussian", lower.tail = TRUE)
您错过了内核中心(数据),内核密度估计器始终需要它。这是更正后的代码:
library(evmix)
x <- c(rnorm(100,-1,0.7),rnorm(100,3,1))
fit = fgkg(x, phiul = FALSE, phiur = FALSE, std.err = FALSE)
prob = pgkg(x, x, fit$lambda, fit$ul, fit$sigmaul, fit$xil, fit$phiul,
fit$ur, fit$sigmaur, fit$xir, fit$phiur)
hist(prob) % now uniform as expected