DeaR R-useRs, I'm trying to fit a logist model with these data:> datiy x 1 1 37 2 1 35 3 1 33 4 1 40 5 1 45 6 1 41 7 1 42 8 0 20 9 0 21 10 0 25 11 0 27 12 0 29 13 0 18 I use glm(), having this output:> g<-glm(y~x,family=binomial,data=dati)Warning messages: 1: Algorithm did not converge in: glm.fit(x = X, y Y, weights = weights, start = start, etastart etastart, 2: fitted probabilities numerically 0 or 1 occurred in: glm.fit(x = X, y = Y, weights = weights, start start, etastart = etastart,> gCall: glm(formula = y ~ x, family = binomial, data dati) Coefficients: (Intercept) x -348.23 11.23 Degrees of Freedom: 12 Total (i.e. Null); 11 Residual Null Deviance: 17.94 Residual Deviance: 7.011e-10 AIC: 4 I don't understand the meaning of warning. Can anyone help me? Many thanks. Cheers, Vito ====Diventare costruttori di soluzioni Became solutions' constructors "The business of the statistician is to catalyze the scientific learning process." George E. P. Box Top 10 reasons to become a Statistician 1. Deviation is considered normal 2. We feel complete and sufficient 3. We are 'mean' lovers 4. Statisticians do it discretely and continuously 5. We are right 95% of the time 6. We can legally comment on someone's posterior distribution 7. We may not be normal, but we are transformable 8. We never have to say we are certain 9. We are honestly significantly different 10. No one wants our jobs Visitate il portale http://www.modugno.it/ e in particolare la sezione su Palese http://www.modugno.it/archivio/palese/
You have a perfect separtaion of y by x, i.e. y == (x>30) is true for all units. Bendix Carstensen ---------------------- Bendix Carstensen Senior Statistician Steno Diabetes Center Niels Steensens Vej 2 DK-2820 Gentofte Denmark tel: +45 44 43 87 38 mob: +45 30 75 87 38 fax: +45 44 43 07 06 bxc at steno.dk www.biostat.ku.dk/~bxc ----------------------> -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Vito Ricci > Sent: Friday, January 28, 2005 11:14 AM > To: r-help at stat.math.ethz.ch > Subject: [R] GLM fitting > > > DeaR R-useRs, > > I'm trying to fit a logist model with these data: > > > dati > y x > 1 1 37 > 2 1 35 > 3 1 33 > 4 1 40 > 5 1 45 > 6 1 41 > 7 1 42 > 8 0 20 > 9 0 21 > 10 0 25 > 11 0 27 > 12 0 29 > 13 0 18 > > I use glm(), having this output: > > > g<-glm(y~x,family=binomial,data=dati) > Warning messages: > 1: Algorithm did not converge in: glm.fit(x = X, y > Y, weights = weights, start = start, etastart > etastart, > 2: fitted probabilities numerically 0 or 1 occurred > in: glm.fit(x = X, y = Y, weights = weights, start > start, etastart = etastart, > > g > > Call: glm(formula = y ~ x, family = binomial, data > dati) > > Coefficients: > (Intercept) x > -348.23 11.23 > > Degrees of Freedom: 12 Total (i.e. Null); 11 Residual > Null Deviance: 17.94 > Residual Deviance: 7.011e-10 AIC: 4 > > I don't understand the meaning of warning. Can anyone > help me? Many thanks. > Cheers, > Vito > > > ====> Diventare costruttori di soluzioni > Became solutions' constructors > > "The business of the statistician is to catalyze > the scientific learning process." > George E. P. Box > > Top 10 reasons to become a Statistician > > 1. Deviation is considered normal > 2. We feel complete and sufficient > 3. We are 'mean' lovers > 4. Statisticians do it discretely and continuously > 5. We are right 95% of the time > 6. We can legally comment on someone's posterior distribution > 7. We may not be normal, but we are transformable > 8. We never have to say we are certain > 9. We are honestly significantly different > 10. No one wants our jobs > > > Visitate il portale http://www.modugno.it/ > e in particolare la sezione su Palese > http://www.modugno.it/archivio/palese/ > > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read > the posting guide! http://www.R-project.org/posting-guide.html >
Vito: Please plot your data: y <- c(1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0) x <- c(37, 35, 33, 40, 45, 41, 42, 20, 21, 25, 27, 29, 18) plot(x, y) You will see that ANY step function between 29 < x < 33 will describe these observations perfectly. Charles Annis, P.E. Charles.Annis at StatisticalEngineering.com phone: 561-352-9699 eFax: 614-455-3265 http://www.StatisticalEngineering.com -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Vito Ricci Sent: Friday, January 28, 2005 5:14 AM To: r-help at stat.math.ethz.ch Subject: [R] GLM fitting DeaR R-useRs, I'm trying to fit a logist model with these data:> datiy x 1 1 37 2 1 35 3 1 33 4 1 40 5 1 45 6 1 41 7 1 42 8 0 20 9 0 21 10 0 25 11 0 27 12 0 29 13 0 18 I use glm(), having this output:> g<-glm(y~x,family=binomial,data=dati)Warning messages: 1: Algorithm did not converge in: glm.fit(x = X, y Y, weights = weights, start = start, etastart etastart, 2: fitted probabilities numerically 0 or 1 occurred in: glm.fit(x = X, y = Y, weights = weights, start start, etastart = etastart,> gCall: glm(formula = y ~ x, family = binomial, data dati) Coefficients: (Intercept) x -348.23 11.23 Degrees of Freedom: 12 Total (i.e. Null); 11 Residual Null Deviance: 17.94 Residual Deviance: 7.011e-10 AIC: 4 I don't understand the meaning of warning. Can anyone help me? Many thanks. Cheers, Vito ====Diventare costruttori di soluzioni Became solutions' constructors "The business of the statistician is to catalyze the scientific learning process." George E. P. Box Top 10 reasons to become a Statistician 1. Deviation is considered normal 2. We feel complete and sufficient 3. We are 'mean' lovers 4. Statisticians do it discretely and continuously 5. We are right 95% of the time 6. We can legally comment on someone's posterior distribution 7. We may not be normal, but we are transformable 8. We never have to say we are certain 9. We are honestly significantly different 10. No one wants our jobs Visitate il portale http://www.modugno.it/ e in particolare la sezione su Palese http://www.modugno.it/archivio/palese/ ______________________________________________ R-help at stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
To push the point a bit further, Vito, if you allow just a bit variation in the data by changing one of the y=1 cases to 0 or one of the y=0 cases to 1, then you'll be able to fit the glm model. If these are real-world data and if you still want to describe them, then a deterministic statement y=1 if x>a y=0 if x<=a where a can be any value between 29 and 33 would work because there is no uncertainty in the model (other than the exact location of a). Tim ---- Original message ---->Date: Fri, 28 Jan 2005 09:55:53 -0500 >From: "Charles Annis, P.E."<Charles.Annis at StatisticalEngineering.com>>Subject: RE: [R] GLM fitting >To: "'Vito Ricci'" <vito_ricci at yahoo.com>,<r-help at stat.math.ethz.ch>> >Vito: > >Please plot your data: > >y <- c(1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0) >x <- c(37, 35, 33, 40, 45, 41, 42, 20, 21, 25, 27, 29, 18) >plot(x, y) > >You will see that ANY step function between 29 < x < 33 willdescribe these>observations perfectly. > > >Charles Annis, P.E. > >Charles.Annis at StatisticalEngineering.com >phone: 561-352-9699 >eFax: 614-455-3265 >http://www.StatisticalEngineering.com > >-----Original Message----- >From: r-help-bounces at stat.math.ethz.ch >[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Vito Ricci >Sent: Friday, January 28, 2005 5:14 AM >To: r-help at stat.math.ethz.ch >Subject: [R] GLM fitting > >DeaR R-useRs, > >I'm trying to fit a logist model with these data: > >> dati > y x >1 1 37 >2 1 35 >3 1 33 >4 1 40 >5 1 45 >6 1 41 >7 1 42 >8 0 20 >9 0 21 >10 0 25 >11 0 27 >12 0 29 >13 0 18 > >I use glm(), having this output: > >> g<-glm(y~x,family=binomial,data=dati) >Warning messages: >1: Algorithm did not converge in: glm.fit(x = X, y >Y, weights = weights, start = start, etastart >etastart, >2: fitted probabilities numerically 0 or 1 occurred >in: glm.fit(x = X, y = Y, weights = weights, start >start, etastart = etastart, >> g > >Call: glm(formula = y ~ x, family = binomial, data >dati) > >Coefficients: >(Intercept) x > -348.23 11.23 > >Degrees of Freedom: 12 Total (i.e. Null); 11 Residual >Null Deviance: 17.94 >Residual Deviance: 7.011e-10 AIC: 4 > >I don't understand the meaning of warning. Can anyone >help me? Many thanks. >Cheers, >Vito > > >====>Diventare costruttori di soluzioni >Became solutions' constructors > >"The business of the statistician is to catalyze >the scientific learning process." >George E. P. Box > >Top 10 reasons to become a Statistician > > 1. Deviation is considered normal > 2. We feel complete and sufficient > 3. We are 'mean' lovers > 4. Statisticians do it discretely and continuously > 5. We are right 95% of the time > 6. We can legally comment on someone's posteriordistribution> 7. We may not be normal, but we are transformable > 8. We never have to say we are certain > 9. We are honestly significantly different > 10. No one wants our jobs > > >Visitate il portale http://www.modugno.it/ >e in particolare la sezione su Palese >http://www.modugno.it/archivio/palese/ > >______________________________________________ >R-help at stat.math.ethz.ch mailing list >https://stat.ethz.ch/mailman/listinfo/r-help >PLEASE do read the posting guide! >http://www.R-project.org/posting-guide.html > >______________________________________________ >R-help at stat.math.ethz.ch mailing list >https://stat.ethz.ch/mailman/listinfo/r-help >PLEASE do read the posting guide!http://www.R-project.org/posting-guide.html