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Hi, Was just wondering if there is any provider for Macros like we have pid provider for function calls? Thanks, Neelam -- This message posted from opensolaris.org

Hello, I wanted to enable tracing in user process. but following example from guide is not working. pid$1::$2:entry { self->trace = 1; } pid$1::$2:return /self->trace/ { self->trace = 0; } pid$1:::entry, pid$1:::return /self->trace/ { } I am getting error like invalid probe description ..... undefined macro variable in probe description. pid$target:user lib:user function:entry

In problem-fixing, the "nicest" problems are those reproducible on demand. Alas, this one is not nice. System: Samba 2.0.6 on Solaris 2.7 (also see similar on Solaris 2.6). Symptom (user perspective): PC suddenly, spontaneously freezes and eventually the connection times out. Symptom (log file): [2000/02/15 09:27:30, 0] ../lib/util_sock.c:read_socket_data(474)

I am trying to test goodness of fit for my legalistic regression using several options as shown below.  Hosmer-Lemeshow test (whose function I borrowed from a previous post), Hosmer–le Cessie omnibus lack of fit test (also borrowed from a previous post), Pearson chi-square test, and deviance test.  All the tests, except the deviance tests, produced p-values well above 0.05.  Would anyone please

...2.23 ...  $ bc           : num  NA NA NA NA NA ...  $ Rsvl         : num  NA NA NA NA NA ...  $ Rftr         : num  NA NA NA NA NA ...  $ Rdefense     : num  NA NA NA NA NA 97 97 97 97 212 ...  $ Rdvc         : num  NA NA NA NA NA ...   Thank you so much for your time and help! Sincerely, Kiyoshi  Sasaki [[alternative HTML version deleted]]

I have a data with binary response variable, repcnd (pregnant or not) and one predictor continuous variable, svl (body size) as shown below. I did Hosmer-Lemeshow test as a goodness of fit (as suggested by a kind “R-helper” previously). To test whether the predictor (svl, or body size) has significant effect on predicting whether or not a female snake is pregnant, I used the differences between

Would anyone help me solve my problem with R, please? I am very new to R. I am doing logistic regression analysis on the presence/absence of salamanders using several predictor variables, as shown below. I have checked my data, but I didn't find any 'NA' or empty cells. When I used step() or stepAIC to select significant predictor variables, <none>s appear to places where