R 如何得到加权数据的威布尔分布

目前，我只能传递一列，即“col”，作为dweibull函数的输入，但我想绘制加权数据的威布尔分布，即传递两列，一列用于数据，另一列用于权重。 我查看了此链接：。但这没有帮助，给了我一个扭曲的情节

#libraries loaded
library(tidyverse)
library(janitor)
library(tibble)
library(stats)
library(fitdistrplus)
library(ggplot2)
library(ggtext)

---

请简化您的帖子，没有人将加载/安装100个软件包。我已经简化了代码，现在只添加了所需的库。如果有人对此查询有任何解决方案，请务必回答。谢谢。请简化您的帖子，没有人将加载/安装100个软件包。我已经简化了代码，现在只添加了所需的库。如果有人对此查询有任何解决方案，请联系我。谢谢。

#functions required
f <- function(k) {
  step <- k
  function(y) seq(0, ceiling(max(y)) + 2, by = step)
}

f1 <- function(k) {
  step <- k
  function(y) seq(0, max(y) + 0.02, by = step)
}

l <- function(y) c(0, ceiling(max(y)) + 2)
l1 <- function(y) c(0, max(y) + 0.02)
```

```
#dataset 
freq_data1<-tibble( "col"= c( 3.9815,3.1105,3.3755,3.0600,3.2765,3.0065,2.7275,2.2970,2.5580,3.2320), 
                    "weight"=c(0.1428571,0.1428571,0.1428571,0.1428571,0.1428571,0.1428571,0.1428571,0.1428571,0.1428571,
                               0.1428571))
```

# **current code** 
#pulling column named "col" 
freq_data1 %>%
  pull(col) ->freq_data

    freq_data[!freq_data %in% 0] -> freq_data
    freq_data %>%
      fitdist(distr = "weibull", method = "mle") -> fit_w  # fits weibull distribution on raw data
    fit_w$estimate[1] %>% round(12) -> w_1  # shape or gamma factor
    fit_w$estimate[2] %>% round(1) -> w_2 # scale or alpha factor
    
    dweibull(x = freq_data, shape = w_1, scale = w_2) -> fwei # density, distribtn, quantile fn (n: number of observations, )
    
    tibble(raw_data = freq_data, freq = fwei) -> df
    min(df$raw_data, na.rm = T) %>% floor() -> min_sel
    max(df$raw_data, na.rm = T) %>% floor() -> max_sel
    
    ggplot(data = df) +
      geom_histogram(data = df, aes(x = raw_data, (y=stat(width*density))), fill = "#361752", color = "#ffbf00", breaks = seq(0,max_sel,0.5)) +
      geom_line(aes(x=raw_data, y=stat(fwei*0.5)), size = 2) +
      labs(x="ws", y = "Frequency [%]") +
      ggtitle(paste0("**System: ", "dummy", "**"),
              subtitle = bquote(atop(bold(.("Frequency Histogram and Weibull Distribution")),
                                     atop(.(paste0("Best-fit Weibull distribution(k = ", round(w_1, 2), ",", " A = ", round(w_2, 2), " m/s)")))))) +
      scale_color_manual(name = "", values = c("brown", "black"), labels = c("Actual Data", "Weibull Distribution")) +
      #theme_minimal() +
      coord_cartesian(clip = "off") +
      theme(legend.position = "none",
            axis.text = element_text(face = "bold", size = 20),
            plot.title = element_markdown(size = 33),
            axis.title = element_text(face = "bold", size = 25),
            legend.text = element_text(face = "bold", size = 20),
            legend.title = element_text(face = "bold", size = 25),
            panel.grid.major = element_line(color = "#F1F1F1", size = 0.3),
            panel.grid.minor = element_line(color = "#F1F1F1", size = 0.05),
            plot.subtitle = element_text(face = "bold", size = 25),
            legend.key = element_rect(fill = "white", color = "white"),
            panel.background = element_rect(fill = "white",
                                            color = "white",
                                            size = 1),
            panel.border = element_blank(),
            axis.line = element_line(colour = "black", size = 0.5, linetype = "solid")) +
      scale_x_continuous(expand = c(0,0), breaks = f(1)) +
      scale_y_continuous(expand = c(0,0),labels = scales::percent_format(accuracy = 1,suffix = ""), limits = l1, breaks = f(0.01)) #-> freq_hist_wei_plot
    
    ```
        Above is my code.With dweibull I cannot pass the "weight" column.I want to get the weibull distribution for weighted data.