все хорошо? Я сталкиваюсь с проблемой настройки бета-распределения, чтобы оно не адаптировалось к данным, а кривая не менялась в зависимости от гистограммы. Коды ниже прилагаются. При определении границы оси x в [0,20] появляется кривая, но как мне отрегулировать ее в интервале по мере следования изображения?
Данные
36.6 33.8 37.8 34.0 32.7 31.8 31.7 36.5 32.7
33.0 36.9 32.6 33.2 34.0 34.3 33.0 30.4 30.0
30.6 30.2 33.6 35.8 35.6 36.8 36.8 33.3 33.2
35.2 35.4 35.0 36.4 36.8 37.4 32.6 32.8 31.4
31.5 34.4 35.2 38.5 38.3 35.9 37.7 34.0 35.6
35.1 32.4 35.6 34.5 34.6 34.7 34.3 32.4 31.8
31.8 36.4 34.1 35.7 34.4 37.1 35.0 31.0 36.5
28.8 28.3 29.4 28.3 30.9 31.3 35.4 34.0 35.9
33.4 33.6 33.3 30.0 32.6 27.0 27.0 26.4 23.8
24.4 26.8 27.6 30.2 28.7 30.4 34.4 35.6 31.0
33.2 36.6 37.9 34.5 35.0 31.5 37.9 36.5 31.0
32.0 32.5 36.2 35.3 33.6 31.9 27.8 31.2 31.8
35.1 36.6 36.8 31.7 30.0 31.5 32.2 34.9 35.7
38.2 38.5 36.2 33.4 33.0 32.0 31.8
library(Hmisc)
library(agricolae)
library(moments)
library(car)
library(MASS)
library(hnp)
library(fitdistrplus)
library(ggplot2)
library(grid)
library(fBasics)
library(VGAM)
dados1=dados$TempMaxima
dados1
####################Estimação dos Modelos########################
Gamm1 = fitdist(data = dados1, distr = "gamma")
summary(Gamm1)
Weibull1 = fitdist(data = dados1, distr = "weibull")
summary(Weibull1)
lnorm1 = fitdist(data = dados1, distr = "lnorm")
summary(lnorm1)
beta1 = fitdist((data=dados1)/40, distr="beta")
summary(beta1)
rm(dgumbel) ## get rid of previous definition
## hack behaviour of VGAM::pgumbel() a little bit
pgumbel <- function(x,...) {
if (length(x)==0) numeric(0) else VGAM::pgumbel(x,...)
}
gumbel1 <- fitdist(dados1, "gumbel",
start=list(location=10, scale=10))
summary(gumbel1)
norm1 = fitdist(data = dados1, distr = "norm")
summary(norm1)
########################### Graphics ###########################
x11()
par(mfrow=c(2,3))
hist(dados1, probability = T, ylab = NULL,
main = "Distribuição Gamma", xlab = NULL, ylim = c(0,0.15),cex = 1.5)
curve(dgamma(x, shape=Gamm1$estimate[1], rate=Gamm1$estimate[2]),
add=T, lwd = 2, lty = 5, col ="red")
hist(dados1, probability = T, ylab = NULL, ylim = c(0,0.15),
main = "Distribuição Weibull ", xlab = NULL, cex = 1.5)
curve(dweibull(x, shape=Weibull1$estimate[1], scale=Weibull1$estimate[2]),
add=T, lwd = 2, col ="red")
hist(dados1, probability = T, ylab = NULL, ylim = c(0,0.15),
main = "Distribuição Log-Normal ", xlab = NULL, cex = 1.5)
curve(dlnorm(x, lnorm1$estimate[1], lnorm1$estimate[2]),
add=T, lwd = 2, lty = 3, col ="red")
hist(dados1, probability = T, ylab = NULL, ylim = c(0,0.15),
main = "Distribuição Gumbel I", xlab = NULL, cex = 1.5)
curve(dgumbel(x, gumbel1$estimate[1], gumbel1$estimate[2]),
add=T, lwd = 2, lty = 2, col ="red")
hist(dados1, probability = T, ylab = NULL, ylim = c(0,0.15),
main = "Distribuição Normal", xlab = NULL, cex = 1.5)
curve(dnorm(x, norm1$estimate[1], norm1$estimate[2]),
add=T, lwd = 2,lty = 4, col ="red")
hist(dados1, probability = T, ylab = NULL,
main = "Distribuição Beta", xlab = NULL, cex = 1.5)
curve(dbeta(x, beta1$estimate[1], beta1$estimate[2]),add=T,lwd = 2,lty = 4)