search for: rohlf

I am using the version of wine that came with RedHat 7.2. I just noticed that Codeweavers has their own distribution of wine that includes what looks like a convenient setup configuration utility. What are the pros and cons of uninstalling what I got from RedHat and downloading and installing the rpm from Codeweavers? Thanks

Hi, I'm trying to figure out how anova works in R by translating the examples in Sokal And Rohlf's (1995 3rd edition) Biometry. I've hit a snag with planned comparisons, their box 9.4 and section 9.6. It's a basic anova design: treatment <- factor(rep(c("control", "glucose", "fructose", "gluc+fruct", "sucrose&quot...

I can run my programs with no problems but the help files do not display. Is there some trick? I am running RH 7.2 with wine installed using the rpm that came with it. Thanks.

...ll be other valuable opinions out there. I have been attempting 2 sample Kolmogorov-Smirnov tests using the ks.test function from the ctest package (ctest v.0.9-15, R v.0.63.3 win32). I am comparing fish length-frequency distributions. My main reference for the KS test at present is Sokal & Rohlf, Biometry (2nd edn), pages 440-445). The individuals in my samples are measured to the nearest 0.5cm and so in most samples there are several identical length values. It appears that the KS test statistic D is being overestimated (and the p value therefore underestimated). I think this is best il...

...dal or uniform data I get a sigmoidal in which the qqnorm() points lie above the qqline() at -ve theoretical quantiles, and the qqnorm() points lie below the qqline() at +ve theoretical quantiles. Yet I expect such platykurtic distributions to go the other way (eg pg 117 in _Biometry_ Sokal & Rohlf, 3rd ed). The same thing with skewed data, I expect right skewed data to show a negatively accelerating shape, but qqnorm() curves upwards. Am I missing something, or is qqnorm() consistently heading in the wrong diirection? Cheers, -P. -- Peter L. Hurd, Ph.D. phurd at uts.cc.utexas.edu http:/...

...SDN card in the Asterisk server), we would like to have Asterisk 'drop' the call completely once it has been returned to the HiPath PBX. I've tried to dig up information on the web, but wasn't able to find out whether that is possible at all - any feedback is appreciated! Marc Rohlfing -- Marc Rohlfing Training Manager OASY AG Heinz-Nixdorf-Ring 1 Geb?ude C 33106 Paderborn Telefon: +49 5251 / 68893 -13 Fax: +49 5251 / 68893 -09 E-Mail: marc.rohlfing@oasy.de Internet: www.oasy.de

...of the F statistics in nested anovas in R. If I understand correctly, the F statistic for the among-subgroups but within groups hypothesis is calculated as MS_subgroups/MS_error, while the F statistic for the factor is calculated as MS_factor/MS_subgroups (I'm getting this from Sokal & Rohlf's _Biometry_). However, as I understand the output from R, it calculates the F for the factor as MS_factor/MS_error, which can significantly change the results. As an example, I took the values from Sokal & Rohlf's example on mosquitos, which are as follows: cage animal length 1...

...ire text of all the messages to the web, I have summarized the results of > this "poll". If you want a copy of all the messages, then drop me an email > and I will forward them! > > AND THE TEXT WINNERS ARE.... There was a clear preference in texts for Zar, > with Sokal and Rohlf coming in second. Most folks thought that Zar was the > best combination of text and reference for undergrads. Many admitted it was > difficult, but that the students could handle it. > > THE SURPRISE WINNER IN THE SOFTWARE CATEGORY: The leader was S-Plus or the > freeware version R....

Dear R-users, I am trying to analyse the data of the box 10.5 in the Biometry from Sokal and Rohlf (2001) using R. This is a three-level nested anova with equal sample size : 3 different treatments are compared ; 2 rats (coded 1 or 2) / treatment are studied ; 3 preparations (coded 1, 2 or 3) / rats are available ; 2 readings of the glycogen content / preparations are realised. Treatment is...

Hi, I made the mistake of upgrading both my Linux box (to Ubuntu 6.06) and Asterisk (to 1.2.9.1) at the same time. Now, when trying to compile mpg123 - using the tried and true "make mpg123" -, the build fails with an error make[3]: Entering directory `/usr/src/asterisk-1.2.9.1/mpg123-0.59r' make[3]: *** No rule to make target `\ ', needed by `mpg123'. Stop. Maybe

...something I've seen requested (and looked to find myself) on this list a few times. It has the same basic syntax as chisq.test(). It does both goodness of fit tests and tests of independence. Yates' and Williams' corrections are implemented. I've put some examples from Sokal & Rohlf up at http://www.psych.ualberta.ca/~phurd/cruft Feedback welcomed, -P. # Kludgy log-likelihood test of independence & goodness of fit # Does Williams' and Yates' correction # # G (TOI) calculation from Zar (2000) Biostatistical Analysis 4th ed. # G (GOF) calculation from Sokal & R...

...e that "continuous distributions do not generate them". Given the problem of "measuring to the nearest..." noted above I frequently find that my data has ties and ks.test generates a warning. I was interested to note that the example of a two-sample KS test given in Sokal & Rohlf's "Biometry" (I have the 2nd edition where the example is on p.441) has exactly the same problem: > A <- c(104,109,112,114,116,118,118,117,121,123,125,126,126,128,128,128) > B <- c(100,105,107,107,108,111,116,120,121,123) > ks.test(A,B) Two-sample Kolmogorov-Sm...

...rary) to find the best power transformation of my data. However, reading the Boxcox help file, I cannot figure out if this function (through its associated log-likelihood function) corrects for * normality only * or if it also induces * homogeneity of variances *. I found in Biometry (Sokal and Rohlf, p. 419) that the box-cox transformation can be extended to induce homogenity of variances in conjunction with Bartlett's test of homogeneity of variances. Does the Boxcox function implemented in R refer to this extension ? Thanks a lot, - - - - - - - - - - - - - - - - - - - - - - - Arnau...

...nalog related. > The layout an all the stuff was free downloadable, so that > you can build your own cards. > Does anybody have the link? you're probably talking about the Zapata Telephony Project and their "Tormenta"-Cards: http://www.zapatatelephony.org/ Marc -- Marc Rohlfing Training Manager OASY AG Heinz-Nixdorf-Ring 1 Geb?ude C 33106 Paderborn Telefon: +49 5251 / 68893 -13 Fax: +49 5251 / 68893 -09 E-Mail: marc.rohlfing@oasy.de Internet: www.oasy.de

...rotocol image: (/usr/lib/divas/te_etsi.2q0) I know from version 2.0 that you had to download these images from either isdn4linux.org or melware.de, yet none of them still have the files available. /usr/lib/divas/ does contain some *etsi* files - do they help somehow? Any hint appreciated. Marc Rohlfing

...ctivated just fine. capiinfo shows all 8 B-channels, so I guess I'm good to go. Maybe this should be stated more clearly in the INSTALL and README files - it's especially confusing for "veterans" who try to do things the 2.1 way... In any case: Thanks for the quick reply. Marc Rohlfing

Hola, tengo una serie de datos datExpr, al usar cor() : cor(datExpr ,method = "pearson", use ="pairwise.complete.obs") me da el siguiente error allocMatrix: too many elements specified Trate con "complete.obs", "na.or.complete", y el resto de las opciones para "use", pero siempre me da algun error.  ¿Alguna idea de como puedo hacer que cor() lea

Hi, I''m trying to understand the lme output and procedure. I''m using the Crawley''s book. I''m try to analyse the rats example take from Sokal and Rohlf (1995). I make a nested analysis using aov following the book. > summary(rats) Glycogen Treatment Rat Liver Min. :125.0 Min. :1 Min. :1.0 Min. :1 1st Qu.:135.8 1st Qu.:1 1st Qu.:1.0 1st Qu.:1 Median :141.0 Median :2 Median :1.5 Median :...

Dear all, I am trying to repeat an example from Sokal and Rohlfs "Biometry" -- Box 11.4, example of a randomized-complete-blocks experiment. The data is fairly simple: series genotype weight 1 pp 0.958 1 pb 0.985 1 bb 0.925 2 pp 0.971 2 pb 1.051 2 bb 0.952 3 pp 0.927 3 pb...

Dear all, During my pre-R era I tried (yes, tried) to understand mixed models by working through the 'rat example' in Sokal and Rohlfs Biometry (2000) 3ed p 288-292. The same example was later used by Crawley (2002) in his Statistical Computing p 363-373 and I have seen the same data being used elsewhere in the litterature. Because this example is so thoroughly described, I thought it would be very interesting to analyse it...