From: <nhy303_at_abdn.ac.uk>

Date: Thu 09 Feb 2006 - 02:27:19 EST

Date: Thu 09 Feb 2006 - 02:27:19 EST

I am trying to fit a generalised least squares model using gls in the nlme
package.

The model seems to fit very well when I plot the fitted values against the original

values, and the model parameters have quite narrow confidence intervals (all are

significant at p<5%).

The problem is that the log likelihood is always given as -Inf. This doesn't seem to make sense because the model seems to fit my data so well. I have checked that the residuals are stationary using an adf test. I can't work out whether

- the model really doesn't fit at all
- there is something in my data that stops the implementation of logLik working correctly (the -Inf value says the calculation hasn't worked)

Possible causes are:

- There are lots of NAs in my data (model and response variables)
- There is some autocorrelation in the data that is not accounted for by the model (most is accounted for).

But, I've tried recreating the problem using a simpler data set, and have never found the same problem.

The command I use to fit the model is...

result2 <- gls(lci4150 ~ propCapInStomachs +

temperature + as.factor(monthNumber) + lagLci1 + lagcap1 + lagcap2, data = monthly, subset = subset1985, na.action = na.approx, weights = varFixed( ~ 1/numob4150) )

The output I get is...

Generalized least squares fit by REML

Model: lci4150 ~ propCapInStomachs + temperature + as.factor(monthNumber) +

lagLci1 + lagcap1 + lagcap2

Data: monthly

Subset: subset1985

AIC BIC logLik

Inf Inf -Inf

Variance function:

Structure: fixed weights

Formula: ~1/numob4150

Coefficients:

Value Std.Error t-value p-value (Intercept) -0.3282412 0.5795665 -0.566356 0.5717 propCapInStomachs 0.0093283 0.0039863 2.340107 0.0202 temperature 0.4342514 0.1526104 2.845490 0.0048 as.factor(monthNumber)2 0.3990717 0.3869991 1.031195 0.3036 as.factor(monthNumber)3 1.3788334 0.3675690 3.751223 0.0002 as.factor(monthNumber)4 1.4037195 0.3857764 3.638686 0.0003 as.factor(monthNumber)5 0.9903316 0.3436177 2.882074 0.0043 as.factor(monthNumber)6 0.3453741 0.3043698 1.134719 0.2577 as.factor(monthNumber)7 0.3948442 0.3035142 1.300909 0.1946 as.factor(monthNumber)8 0.5021812 0.3532413 1.421638 0.1565 as.factor(monthNumber)9 -0.0794319 0.3598981 -0.220707 0.8255 as.factor(monthNumber)10 0.3536805 0.3790538 0.933061 0.3518 as.factor(monthNumber)11 0.7874834 0.3557116 2.213826 0.0278 as.factor(monthNumber)12 0.1854279 0.3178320 0.583415 0.5602 lagLci1 0.5488437 0.0576144 9.526151 0.0000 lagcap1 0.0110994 0.0043669 2.541714 0.0117 lagcap2 -0.0088080 0.0041099 -2.143127 0.0332

Does anyone have any suggestions of how I can get a meaningful value for logLik? Or some other way that I can compare models.

Thankyou for your help,

Lillian.

-- Lillian Sandeman PhD Student School of Biological Sciences University of Aberdeen AB24 2TZ Tel.: 01224 272648 E-mail: l.sandeman@abdn.ac.uk ______________________________________________ R-help@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.htmlReceived on Thu Feb 09 03:49:50 2006

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