search for: 136.1

What fun. I don't often stoke up the boiler and actually compile open-source code, but here I am at the beginning of just such a joyous and wondrous adventure. I'm running the latest level of AIX (V5.3...V4.3 has been obsolete for at least, what, 5 years) and using the IBM compiler (xlc is similarly obsolete, from back when the compiler came with the O/S...oh, for the halcyon days of

Hi I have a data frame like this: V1 V2 V3 V4 Min. :0.01146 Min. :0.0006714 Min. :0.004912 Min. : 0 1st Qu.:0.03938 1st Qu.:0.0072805 1st Qu.:0.052719 1st Qu.:1150 Median :0.04224 Median :0.0077581 Median :0.056388 Median :1150 Mean :0.04010 Mean :0.0074669 Mean :0.052602 Mean :1173 3rd

Hi all, How can we use ks.test() to evaluate goodness of fit of mixtures of distributions? For example I have the following dataset: > x [1] 176.1 176.8 259.6 171.6 90.0 234.3 145.7 113.7 105.9 176.2 168.9 136.1 [13] 109.2 110.3 164.3 117.7 131.3 163.7 200.4 196.4 196.2 168.6 190.4 127.5 [25] 136.0 114.2 112.0 91.9 333.4 295.5 172.0 293.3 91.7 289.7 118.8 55.1 [37] 161.9 233.9 197.7

I have two questions: 1. If I want to do a binomial logit, how to handle the categorical response variable? Data for the response variables are not numerical, but text. 2. What if I want to do a multinomial logit, still with categorical response variable? The variable has 5 non-numerical response levels, I have to do it with a multinomial logit. Any input is highly appreciated! Thanks! Ed

Hello, thanks for looking over my ramblings... We have an NT4 PDC with and NT4 BDC on 192.168.132.X, these boxes are very very old and overloaded. I am trying to replace them with a nice shinny new Samba box. My problem is that while I am trying to test it out to make sure it plays nice it keeps winning the elections. I find this weird as I have set the box to domain master = no and turned the

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