2021-06-15

plot(x,y)
# Set seed for fixing 1 simulation
set.seed(1)
# Simulate the x values
# length.out：这个序列的输出长度。
simx=seq(min(x),max(x),length.out=length(x))
# Model the y values y=12+ke^(-x), with a starting value of k 
model = nls(y~12+k*exp(-simx), start=list(k=500))
summary(model)
# Add model to scatter plot
lines(simx,predict(model),lty=2,col="green",lwd=3)

 随机抽样函数sample（）

sample（x，size，replace=FALSE，prob=NULL）

x　　随机样本的向量

size　　抽取样本的数量

replace　　重复抽样与否，FALSE不放回，TRUE（T)放回

prob　　等可能事件与否，NULL表示等可能，prob=y，y为和x中各个向量对应的概率

1）52张牌中随机抽4张，不放回、放回

> sample(52,4)
[1] 40 30 49 25
> sample(52,4, replace=T)
[1] 45  9  5  6

2）一枚硬币随机抛10次，正面和反面的随机模拟

> sample(c("Z","F"), 10, replace=T)
 [1] "F" "Z" "F" "Z" "F" "F" "Z" "F" "F" "F"
> sample(c("Z","F"), 10, replace=T)
 [1] "Z" "F" "F" "Z" "Z" "F" "Z" "F" "Z" "Z"

3）10次手术成功的概率为0.8的随机模拟

> sample(c(0,1), 10, replace=T, prob=c(0.2,0.8))
 [1] 1 1 1 1 0 1 0 1 1 1
> sample(c(0,1), 10, replace=T, prob=c(0.2,0.8))
 [1] 1 1 1 0 1 1 1 1 1 1

```![](https://img.haomeiwen.com/i13248401/a28d5737be8afed7.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240)
https://www.jianshu.com/p/7d7862c72c4a

二項分佈
https://blog.csdn.net/csdnxiaobaitiao/article/details/99679679


https://blog.csdn.net/weixin_45126863/article/details/99695230