Python 生成和排序随机变量的 4 例错误

Question

我正在尝试在 Python 中模拟连续随机生成的数字分布，并找到组合数字（其中 y=x1+x2）在 p(0.9

n = 10000
x11 = [random.random() for i in range(n)]
x12 = [random.random() for i in range(n)]
x21 = [-0.5*(log(1-random.random())) for i in range(n)]
x22 = [-0.5*(log(1-random.random())) for i in range(n)]
x31 = [random.random() for i in range(n)]
x32 = [random.uniform(0,2) for i in range(n)]
x41 = [0.25 if random.random() < 0.8 else 1.5 for r in range(n)]
x42 = [0.25 if random.random() < 0.8 else 1.5 for r in range(n)]

x11 到 x42 是我试图获得它们介于 0.9 和 1.8 之间的概率的情况，其中生成的列表对被组合然后对其进行操作。所以将 x11 和 x12 组合起来，然后找到期望值、方差和 0.9 到 1.8 p(x)。

def test():
  x1,x2,c = 0.0,0.0,0.0
  for i in range(10000):
    if random.random()< 0.8:
      x1 += 0.25
    else:
      x2 += 1.5
    y = x1 + x2
    if y>0.9 and y<=1.8:
      c = c + 1
  return x1,x2,c

print "test: ",test()

def sim(a,b):
  #pyab1 = sum([a for a in a if a>0.9 and a<=1.8])/10000
  #pyab2 = sum([b for b in b if b>0.9 and b<=1.8])/10000
  #print "*****",float(pyab1+pyab2)
  #print a+b
  #array1 = [[a],[b]]
  array1 = a+b
  #array1.extend(a)
  #array1.extend(b)
  #c = 0
  #for y in array1:
    #if y>0.9 and y<=1.8:
      #c = c + 1
  pyab = sum([y for y in array1 if y>0.9 and y<=1.8])/10000
  print("P(a < x <= b) : {0:8.4f}".format(pyab))

我只计算概率 P(0.9

y~u(0,1) = 0.575

y~exp(2) = 0.3371

x1~u(0,1) x2~u(0,2)

P(y=0.25)=0.8 P(y=1.5)=0.2 = 0.2

这是输出，后面是它应该给出的值，但这显示了结果有多远。

case 1: P(a < x <= b) : 0.7169 #should be 0.575 
case 2: P(a < x <= b) : 0.4282 #should be 0.3371 
case 3: P(a < x <= b) : 0.5966 #should be 0.4413 
case 4: P(a < x <= b) : 0.5595 #should be 0.2 

我对 Python 很陌生，所以如果我的问题似乎有我错过的明显解决方案，请耐心等待。

Answer 1

很可能你最好更换

pyab = sum([y for y in array1 if y>0.9 and y<=1.8])/10000

与

pyab = len([y for y in array1 if y>0.9 and y<=1.8])/len(array1)

因为您需要概率，而不是实际值的总和。另外，len(array1) 很可能不是 10000，而是两个数组的总长度。