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R 贝叶斯推理中定性数据的定量化_R_Statistics_Bayesian_Inference - Fatal编程技术网

R 贝叶斯推理中定性数据的定量化

R 贝叶斯推理中定性数据的定量化,r,statistics,bayesian,inference,R,Statistics,Bayesian,Inference,我有一个场景,其中问了5个问题。答案是二进制的1-是和0-否。我根据它们的总和创建了一个预测类,预测最终结果的可能性 library(dplyr) library(ggplot2) library(plotly) library(purrr) library(ggjoy) library(forcats) Question1 <- "Does source A state XYZ?" Question2 <- "Does source B state

我有一个场景,其中问了5个问题。答案是二进制的1-是和0-否。我根据它们的总和创建了一个预测类,预测最终结果的可能性

library(dplyr)
library(ggplot2)
library(plotly)
library(purrr)
library(ggjoy)
library(forcats)

Question1 <- "Does source A state XYZ?"
Question2 <- "Does source B state XYZ?"
Question3 <- "Does source A state QRS?"
Question4 <- "Does source B state QRS?"
Question5 <- "Does source C state MNO?"
Conclusion <- "How likely is situation X to happen?"

Date <- seq.Date(from = as.Date("2020-01-01"), to = as.Date("2020-5-29"), by = "day")
Q1 <- sample(0:1, length(Date), replace = T, prob = c(0.4, 0.6))
Q2 <- sample(0:1, length(Date), replace = T, prob = c(0.5, 0.5))
Q3 <- sample(0:1, length(Date), replace = T, prob = c(0.5,0.5))
Q4 <- sample(0:1, length(Date), replace = T, prob = c(0.5, 0.5))
Q5 <- sample(0:1, length(Date), replace = T, prob = c(0.4, 0.6))

sample_df <- data.frame(Q1, Q2, Q3, Q4, Q5)
sample_df$Sum <- rowSums(sample_df)
sample_df %>% mutate(Conclusion = case_when(Sum == 5 ~ "Almost Certain",
                                            Sum == 4 ~ "Very Likely",
                                            Sum == 3 ~ "Likely",
                                            Sum == 2 ~ "Unlikely",
                                            Sum == 1 ~ "Very Unlikely",
                                            Sum == 0 ~ "Remote")) -> sample_df

sample_df <- cbind(Date, sample_df) %>% arrange(Date)
库(dplyr)
图书馆(GG2)
图书馆(绘本)
图书馆(purrr)
图书馆(ggjoy)
图书馆(供猫用)

问题1:是否有观察到的结果?这似乎是唯一的预测因素。