[R] GLM fitting
Tim F Liao
tfliao at uiuc.edu
Fri Jan 28 16:38:58 CET 2005
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 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:
>
>> 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
>
>
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