开发者:上海品职教育科技有限公司 隐私政策详情

应用版本:4.2.11(IOS)|3.2.5(安卓)APP下载

Roxanne_104 · 2020年06月24日

问一道题:NO.PZ2018122801000073

问题如下:

Richard Frank, FRM, is running a regression model to forecast in-sample data. He is concerned about data mining and over-fitting the data. Which of the following criteria provides the highest penalty factor based on degrees of freedom?

选项:

A.

Mean squared error (MSE)

B.

Unbiased mean squared error (s2)

C.

Akaike information criterion (AIC)

D.

Schwarz information criterion (SIC)

解释:

D is correct.

考点 Selecting Forecasting Models

解析 The Schwarz information criterion (SIC) has the highest penalty factor. The mean squared error (MSE) does not penalize the regression model based on the increased number of parameters, k. The penalty factors for s2, AIC, and SIC are (T/T  k), e(2k/T), and T(k/T), respectively. Thus, SIC has the greatest penalty factor.

看了解析,这题太难理解了。可不可以直接记结论

1 个答案

袁园_品职助教 · 2020年06月28日

可以!

  • 1

    回答
  • 0

    关注
  • 499

    浏览
相关问题

NO.PZ2018122801000073问题如下 Richard Frank, FRM, is running a regression mol to forecast in-sample tHe is concerneabout ta mining anover-fitting the tWhiof the following criteria provis the highest penalty factor baseon grees of freem? Mean squareerror (MSE) Unbiased mesquareerror (s2) Akaike information criterion (AI Schwarz information criterion (SI is correct. 考点 : Selecting Forecasting Mols 解析 : The Schwarz information criterion (SIhthe highest penalty factor. The mesquared error (MSE) es not penalize the regression mol baseon the increased number of parameters, k. The penalty factors for s2, AIand SIC are (T/T –  k), e(2k/T), anT(k/T), respectively. Thus, SIC hthe greatest penalty factor. 这道题什么意思啊??

2024-05-07 19:46 2 · 回答

NO.PZ2018122801000073 问题如下 Richard Frank, FRM, is running a regression mol to forecast in-sample tHe is concerneabout ta mining anover-fitting the tWhiof the following criteria provis the highest penalty factor baseon grees of freem? Mean squareerror (MSE) Unbiased mesquareerror (s2) Akaike information criterion (AI Schwarz information criterion (SI is correct. 考点 : Selecting Forecasting Mols 解析 : The Schwarz information criterion (SIhthe highest penalty factor. The mesquared error (MSE) es not penalize the regression mol baseon the increased number of parameters, k. The penalty factors for s2, AIand SIC are (T/T –  k), e(2k/T), anT(k/T), respectively. Thus, SIC hthe greatest penalty factor. 如题,谢谢~

2024-01-26 16:48 1 · 回答

NO.PZ2018122801000073 问题如下 Richard Frank, FRM, is running a regression mol to forecast in-sample tHe is concerneabout ta mining anover-fitting the tWhiof the following criteria provis the highest penalty factor baseon grees of freem? Mean squareerror (MSE) Unbiased mesquareerror (s2) Akaike information criterion (AI Schwarz information criterion (SI is correct. 考点 : Selecting Forecasting Mols 解析 : The Schwarz information criterion (SIhthe highest penalty factor. The mesquared error (MSE) es not penalize the regression mol baseon the increased number of parameters, k. The penalty factors for s2, AIand SIC are (T/T –  k), e(2k/T), anT(k/T), respectively. Thus, SIC hthe greatest penalty factor. 印象里只有AIC和BIC,知识点可能有遗漏,烦请老师说明下。谢谢!

2023-04-19 16:22 1 · 回答

NO.PZ2018122801000073 问题如下 Richard Frank, FRM, is running a regression mol to forecast in-sample tHe is concerneabout ta mining anover-fitting the tWhiof the following criteria provis the highest penalty factor baseon grees of freem? Mean squareerror (MSE) Unbiased mesquareerror (s2) Akaike information criterion (AI Schwarz information criterion (SI is correct. 考点 : Selecting Forecasting Mols 解析 : The Schwarz information criterion (SIhthe highest penalty factor. The mesquared error (MSE) es not penalize the regression mol baseon the increased number of parameters, k. The penalty factors for s2, AIand SIC are (T/T –  k), e(2k/T), anT(k/T), respectively. Thus, SIC hthe greatest penalty factor. 答案说The mesquareerror (MSE) es not penalize the regression mol后面又说The penalty factors for s2 are (T/T k)那到底有没有惩罚呢

2022-05-27 17:29 3 · 回答

NO.PZ2018122801000073

2022-03-02 12:52 1 · 回答