Question

我使用多项logit模型作为概率函数来模拟特定代理集的选择，当我计算出P1，P2和P3的概率以及我如何使用这些概率时，我的问题就出现了。实际建模选择。我的想法是使用类似于模型库中的彩票获取示例，但问题在于，在这种情况下，概率未设置但是每个滴答都会改变，即使P1具有最低的发生机会，它也可能具有最高的机会。下一次迭代。谢谢你的帮助。

PS。对于每种情况，多项Logit的Eq是P {ik} = {exp（utilityik）\ sum exp（utilityjk）}。

to flightchoice-business

let flight-time1 mean [time1] of airline1
let airfare-airline1 mean [airfare] of airline1

set beta1 .8
set beta2 .2

set utility1 beta1 * (airfare-airline1) + beta2 * abs((time - flight-time1) * 10)

let flight-time2 mean [time1] of airline2
let airfare-airline2 mean [airfare] of airline2

set beta1 .8
set beta2 .2

set utility2 beta1 * (airfare-airline2) + beta2 * abs((time - flight-time2) * 10)

let flight-time3 mean [time1] of airline3
let airfare-airline3 mean [airfare] of airline3

set beta1 .8
set beta2 .2

set utility3 beta1 * (airfare-airline3) + beta2 * abs((time - flight-time3) * 10)

let cumulsum exp(utility1) + exp(utility2) + exp(utility3)

let P1 exp(utility1) / cumulsum

let P2 exp(utility2) / cumulsum

let P3 exp(utility3) / cumulsum

let buy random-float P1 + P2 + P3




end

Answer 1

你走在正确的轨道上。您的代码应继续如下：

...
let buy random-float P1 + P2 + P3
ifelse buy < P1 [
  do-stuff-with-P1
] [
  ifelse buy < P1 + P2 [
    do-stuff-with-P2
  ] [
    do-stuff-with-P3
  ]
]

你可以用一个列表的函数来概括它，在我看来它更好一些：

to-report weighted-random [ weights ]
  let pick random-float sum weights
  let total 0
  let i 0
  foreach weights [
    set total total + ?
    if pick < total [ report i ]
    set i i + 1
  ]
end

您可以按如下方式使用：

let buy weighted-random (list P1 P2 P3)
if buy = 0 [ do-stuff-with-P1 ]
if buy = 1 [ do-stuff-with-P2 ]
if buy = 2 [ do-stuff-with-P3 ]

多项Logit /建模选择[Netlogo]

1 个答案: