Hi Hadassa, > Random effects: > Formula: ~1 | id > (Intercept) Residual > StdDev: 4.240752 1.240242 > > Correlation Structure: Gaussian spatial correlation > Formula: ~age | id > Parameter estimate(s): > range > 4.662006
it looks to me as though you have two variance parameters and the Gaussian variogram. I speculate that the model that you've written is not quite the model that you've fit. I see no provision for sigma in your lme statement. Note p. 230 of Pinheiro and Bates, which says that "The within-group errors can be standardized to have unit variance, without changing their correlation structure". Probably sigma is confounded with tau. If my interpretation is correct, then nu = 4.240752 tau = 1.240242 and tau also has your sigma in there. Then the p parameter for your Gaussian semivariogram is 4.662006. I hope that this helps, Andrew -- Andrew Robinson Ph: 208 885 7115 Department of Forest Resources Fa: 208 885 6226 University of Idaho E : [EMAIL PROTECTED] PO Box 441133 W : http://www.uidaho.edu/~andrewr Moscow ID 83843 Or: http://www.biometrics.uidaho.edu No statement above necessarily represents my employer's opinion. ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
