search for: stressplot

Displaying 4 results from an estimated 4 matches for "stressplot".

2010 May 06
1
how to extract from obj. created by plot function stressplot without printing plot?
hello, i'd like to extract values from stressplot, but as this should happen within a long run of code, which also does a multiple plot, i need to prevent stressplot to print to the device. i tried ..,plot=F), but this is useless. any advise on this? thanks, kay ----- ------------------------ Kay Cichini Postgraduate student Institute of Bot...
2013 Apr 26
1
NMDS in Vegan: problems in stressplot, best solution
Hello, I can draw a basic stress plot for NMDS with the following code in package Vegan. > stressplot(parth.mds, parth.dis) When I try to specify the line and point types, it gives me error message. > stressplot(parth.mds, parth.dis, pch=1, p.col="gray", lwd=2, l.col="red") Error in plot.xy(xy, type, ...) : invalid plot type In the above code, if I removed line type, it doe...
2010 Jul 22
1
interpretation of stress in NMDS
Among those users of Primer, stress values greater than 0.3 are interpreted as "questionable". Using both isoMDS and metaMDS (vegan package), the stress values returned are much higher using my own data and using examples provided in R Help. For example Rstress = 8.3, and the stressplot r2 = 0.99 indicating (to me) that the ordination is OK. I am guessing that the "stress" values across packages are not the same, and googling about has not returned a satisfactory answer ... thus this posting. My concern being that reporting a stress value of 8 for what I consider a sati...
2009 Sep 01
1
Logistic Politomic Regression in R
...tinuing from the above S <- Shepard(Dij, Dnmds$points) plot(S) lines(yf ~ x, data = S, type = "S", col = "blue", lwd = 2) You can also compute some measures to help understand how well the nMDS distances reflect the original distances. ## Note, these are taken from function stressplot in the vegan package ## written by Jari Oksanen, which uses isoMDS from package MASS ## internally. ## you might want to look at metaMDSiter() in that package to do random ## starts to check you haven't converged to a sub-optimal local solution (stress <- sum((S$y - S$yf)^2) / sum(S$y^2)) ##...