similar to: Higher log-likelihood in null vs. fitted model

Displaying 5 results from an estimated 5 matches similar to: "Higher log-likelihood in null vs. fitted model"

2012 Sep 18
1
Cochran-Mantel-Haenszel test
Hello, I have some satellite tag time-at-depth (TAD) frequency data that I would like some help with. The data was transmitted via satellite as percent time spent in each of 7 depth bins (0m, 0-1m, 1-10m, 10-50m etc.), binned over 6-hour intervals. I categorized each row of data corresponding to a date and time into summer vs. winter, and day vs. night, and then summed and averaged the given
2007 Aug 30
15
ZFS, XFS, and EXT4 compared
I have a lot of people whispering "zfs" in my virtual ear these days, and at the same time I have an irrational attachment to xfs based entirely on its lack of the 32000 subdirectory limit. I''m not afraid of ext4''s newness, since really a lot of that stuff has been in Lustre for years. So a-benchmarking I went. Results at the bottom:
2011 Jun 24
3
Error using betareg
Dear all, I get an error using betrag on this data set :http://dl.dropbox.com/u/1866110/dump.csv. I run it like this regression f2.1=betareg(Y~X1+X2,data=dump) summary(f2.1) I get : Call: betareg(formula = Y ~ X1 + X2, data = dump) Standardized weighted residuals 2: Error in quantile.default(x$residuals) : missing values and NaN's not allowed if 'na.rm' is FALSE In addition:
2007 Dec 08
0
help for segmented package
Hi, I am trying to find m breakpoints of a linear regression model. I used the segmented package. It works fine for small number of predicators and breakpoints.(3 r.v. 3 points). However, my model has 14 variables it even would not work even for just one breakpoints!. The error message is always estimated breakpoints are out of range. Since my problem is time related problem. So I
2011 Nov 11
2
Estimating IRT models by using nlme() function
Hi, I have a question about estimating IRT models by using nlme, not just rasch model, but also other models. Behavior Research Methods <http://www.springerlink.com/content/1554-351x/> Volume 37, Number 2 <http://www.springerlink.com/content/1554-351x/37/2/>, 202-218, DOI: 10.3758/BF03192688 Using SAS PROC NLMIXED to fit item response theory models (2005). Ching-Fan