Robust Regression Model in R

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  • เผยแพร่เมื่อ 4 ธ.ค. 2024

ความคิดเห็น • 20

  • @DDosAndDonts
    @DDosAndDonts ปีที่แล้ว +1

    Thank you very much. Such a clear and concise video

  • @moliso
    @moliso 2 ปีที่แล้ว +1

    Thank you for this lesson! Very helpful!

  • @vanillamintchip8494
    @vanillamintchip8494 2 ปีที่แล้ว +1

    This helped me a lot! Thank you!

  • @sihabsojib7888
    @sihabsojib7888 2 ปีที่แล้ว +1

    Thanks for your help, sir.

  • @nealdorelis5703
    @nealdorelis5703 ปีที่แล้ว +1

    Nice! Do have a video about robust regression done with Huber-White-Hinkley (HC1) ?

  • @caduguimaraes
    @caduguimaraes ปีที่แล้ว +1

    Thanks

  • @TABandiTA
    @TABandiTA 2 ปีที่แล้ว +1

    Thank you very much, it was realy interesting!

  • @leaschiemann5080
    @leaschiemann5080 3 หลายเดือนก่อน

    Thank you very much! Can I use lmrob if my predictor is categorical?

    • @RegorzStatistik
      @RegorzStatistik  3 หลายเดือนก่อน

      I haven't tried it yet, but with a binary predictor it should work. For more of two categories you need dummy coding and I don't know whether lmrob builds those automatically or whether you have to do this before running the robust regression.

  • @debayankoley5844
    @debayankoley5844 ปีที่แล้ว +1

    The adjusted R squared in robust regression is negative and less than the OLS, does that mean it’s not a good fit?

    • @RegorzStatistik
      @RegorzStatistik  ปีที่แล้ว +1

      I would only interpret adjusted R squared when comparing two or more models with different numers of predictors.

  • @aplysiaenelpaisdelasmaravi7547
    @aplysiaenelpaisdelasmaravi7547 ปีที่แล้ว +2

    there is no pvalue for the significance of the over all model. Isn't that necesary in robust regression? how can you tell that the model is significant?

    • @RegorzStatistik
      @RegorzStatistik  ปีที่แล้ว

      I think in most situations the overall significance of the model isn't really that interesting. Yes, we report it in a multiple regression, but often only in the notes to the regression table. It is quite rarely the case that one has a hypothesis about the overall model; most hypotheses are based on specific regression weights only. So for me this limitation has not been relevant in my analyses, yet.

    • @aplysiaenelpaisdelasmaravi7547
      @aplysiaenelpaisdelasmaravi7547 ปีที่แล้ว

      @@RegorzStatistik I agree, however journals frecuently demand it. I founded later that some people use an ANOVA WALD test comparing the model with an only intercept y~1 vs y~1+1m+²m+3m. If anyone is interested.

  • @shubhrachoudhary9450
    @shubhrachoudhary9450 4 หลายเดือนก่อน

    how to make a prediction model from the robust regression results

    • @RegorzStatistik
      @RegorzStatistik  4 หลายเดือนก่อน

      I haven't used it for that, yet. But you do get regression weights as a result of the robust regression. I think you could use those for prediction purposes.

  • @shubhrachoudhary9450
    @shubhrachoudhary9450 4 หลายเดือนก่อน

    if the intercept is significant what does it imply? should the intercept be significant of insignificant?

    • @RegorzStatistik
      @RegorzStatistik  4 หลายเดือนก่อน

      The same as in the OLS regression: That the intercept is different from zero (which is in 99% of the cases not very interesting).