How to obtain individual log-likelihood value from glm?

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How to obtain individual log-likelihood value from glm?

 Dear R-help, The function logLik can be used to obtain the maximum log-likelihood value from a glm object. This is an aggregated value, a summation of individual log-likelihood values. How do I obtain individual values? In the following example, I would expect 9 numbers since the response has length 9. I could write a function to compute the values, but there are lots of family members in glm, and I am trying not to reinvent wheels. Thanks! counts <- c(18,17,15,20,10,20,25,13,12)      outcome <- gl(3,1,9)      treatment <- gl(3,3)      data.frame(treatment, outcome, counts) # showing data      glm.D93 <- glm(counts ~ outcome + treatment, family = poisson())      (ll <- logLik(glm.D93))         [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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Re: How to obtain individual log-likelihood value from glm?

 If you look at stats:::logLik.glm  #3 ":" because it's unexported, as is true of most methods it should be obvious. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Tue, Aug 25, 2020 at 8:34 AM John Smith <[hidden email]> wrote: > Dear R-help, > > The function logLik can be used to obtain the maximum log-likelihood value > from a glm object. This is an aggregated value, a summation of individual > log-likelihood values. How do I obtain individual values? In the following > example, I would expect 9 numbers since the response has length 9. I could > write a function to compute the values, but there are lots of > family members in glm, and I am trying not to reinvent wheels. Thanks! > > counts <- c(18,17,15,20,10,20,25,13,12) >      outcome <- gl(3,1,9) >      treatment <- gl(3,3) >      data.frame(treatment, outcome, counts) # showing data >      glm.D93 <- glm(counts ~ outcome + treatment, family = poisson()) >      (ll <- logLik(glm.D93)) > >         [[alternative HTML version deleted]] > > ______________________________________________ > [hidden email] mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help> PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code. >         [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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Re: How to obtain individual log-likelihood value from glm?

 In reply to this post by John Smith-5 If you don't worry too much about an additive constant, then half the negative squared deviance residuals should do. (Not quite sure how weights factor in. Looks like they are accounted for.) -pd > On 25 Aug 2020, at 17:33 , John Smith <[hidden email]> wrote: > > Dear R-help, > > The function logLik can be used to obtain the maximum log-likelihood value > from a glm object. This is an aggregated value, a summation of individual > log-likelihood values. How do I obtain individual values? In the following > example, I would expect 9 numbers since the response has length 9. I could > write a function to compute the values, but there are lots of > family members in glm, and I am trying not to reinvent wheels. Thanks! > > counts <- c(18,17,15,20,10,20,25,13,12) >     outcome <- gl(3,1,9) >     treatment <- gl(3,3) >     data.frame(treatment, outcome, counts) # showing data >     glm.D93 <- glm(counts ~ outcome + treatment, family = poisson()) >     (ll <- logLik(glm.D93)) > > [[alternative HTML version deleted]] > > ______________________________________________ > [hidden email] mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code. -- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Office: A 4.23 Email: [hidden email]  Priv: [hidden email] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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Re: How to obtain individual log-likelihood value from glm?

 Thanks Peter for a very promising tip. On Tue, Aug 25, 2020 at 11:40 AM peter dalgaard <[hidden email]> wrote: > If you don't worry too much about an additive constant, then half the > negative squared deviance residuals should do. (Not quite sure how weights > factor in. Looks like they are accounted for.) > > -pd > > > On 25 Aug 2020, at 17:33 , John Smith <[hidden email]> wrote: > > > > Dear R-help, > > > > The function logLik can be used to obtain the maximum log-likelihood > value > > from a glm object. This is an aggregated value, a summation of individual > > log-likelihood values. How do I obtain individual values? In the > following > > example, I would expect 9 numbers since the response has length 9. I > could > > write a function to compute the values, but there are lots of > > family members in glm, and I am trying not to reinvent wheels. Thanks! > > > > counts <- c(18,17,15,20,10,20,25,13,12) > >     outcome <- gl(3,1,9) > >     treatment <- gl(3,3) > >     data.frame(treatment, outcome, counts) # showing data > >     glm.D93 <- glm(counts ~ outcome + treatment, family = poisson()) > >     (ll <- logLik(glm.D93)) > > > >       [[alternative HTML version deleted]] > > > > ______________________________________________ > > [hidden email] mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help> > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html> > and provide commented, minimal, self-contained, reproducible code. > > -- > Peter Dalgaard, Professor, > Center for Statistics, Copenhagen Business School > Solbjerg Plads 3, 2000 Frederiksberg, Denmark > Phone: (+45)38153501 > Office: A 4.23 > Email: [hidden email]  Priv: [hidden email] > > > > > > > > > >         [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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Re: How to obtain individual log-likelihood value from glm?

 In reply to this post by Peter Dalgaard-2 If the weights < 1, then we have different values! See an example below. How  should I interpret logLik value then? set.seed(135)  y <- c(rep(0, 50), rep(1, 50))  x <- rnorm(100)  data <- data.frame(cbind(x, y))  weights <- c(rep(1, 50), rep(2, 50))  fit <- glm(y~x, data, family=binomial(), weights/10)  res.dev <- residuals(fit, type="deviance")  res2 <- -0.5*res.dev^2  cat("loglikelihood value", logLik(fit), sum(res2), "\n") On Tue, Aug 25, 2020 at 11:40 AM peter dalgaard <[hidden email]> wrote: > If you don't worry too much about an additive constant, then half the > negative squared deviance residuals should do. (Not quite sure how weights > factor in. Looks like they are accounted for.) > > -pd > > > On 25 Aug 2020, at 17:33 , John Smith <[hidden email]> wrote: > > > > Dear R-help, > > > > The function logLik can be used to obtain the maximum log-likelihood > value > > from a glm object. This is an aggregated value, a summation of individual > > log-likelihood values. How do I obtain individual values? In the > following > > example, I would expect 9 numbers since the response has length 9. I > could > > write a function to compute the values, but there are lots of > > family members in glm, and I am trying not to reinvent wheels. Thanks! > > > > counts <- c(18,17,15,20,10,20,25,13,12) > >     outcome <- gl(3,1,9) > >     treatment <- gl(3,3) > >     data.frame(treatment, outcome, counts) # showing data > >     glm.D93 <- glm(counts ~ outcome + treatment, family = poisson()) > >     (ll <- logLik(glm.D93)) > > > >       [[alternative HTML version deleted]] > > > > ______________________________________________ > > [hidden email] mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help> > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html> > and provide commented, minimal, self-contained, reproducible code. > > -- > Peter Dalgaard, Professor, > Center for Statistics, Copenhagen Business School > Solbjerg Plads 3, 2000 Frederiksberg, Denmark > Phone: (+45)38153501 > Office: A 4.23 > Email: [hidden email]  Priv: [hidden email] > > > > > > > > > >         [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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Re: How to obtain individual log-likelihood value from glm?

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Re: How to obtain individual log-likelihood value from glm?

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Re: How to obtain individual log-likelihood value from glm?

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