Re: [R-sig-eco] number of observations used in scatterplot.matrix()
Hi, maybe something like this should do the trick:
n - nrow(x)
txt - paste(rho=, txt, \np=,pval, n=, n, sep=)
HTH
Luciano
2011/1/21 Maria Dulce Subida mdsub...@icman.csic.es
Dear all,
I have a script (please see below) that gives a scatter plot matrix on
the upper panel, and the spearman rho and probability values on the
lower panel. It also gives the density function of each variable in the
diagonal, adds a smoother and a linear regression line to each scatter
plot, and puts significant spearman coefficient values in red.
Now I would like to add to the lower panel information, the value of
n=number of observations used to calculate the spearman correlation
coefficient. Does anyone know I could I add that parameter to my
function panel.cor?
Thank you!
Kind regards,
Dulce
panel.cor - function (x, y,method=spearman,digits=2,...)
{
points(x,y,type=n);
usr - par(usr); on.exit(par(usr))
par(usr = c(0, 1, 0, 1));
correl - cor.test(x, y,method=method);
r=correl$estimate;
pval=correl$p.value;
color=black;
if (pval0.05) color=red;
txt - format(r,digits=2)
pval - format(pval,digits=2)
n - nrow(x)
txt - paste(rho=, txt, \np=,pval, n=, n, sep=)
text(0.5, 0.5, txt,col=color)
}
scatterplot.matrix (~ var1 + var2 + var3 , data=mydata,
main=Mydata, smooth=TRUE,
lower.panel=panel.cor, pch=20, cex=0.5,
col=c(red,black),cex.labels=1, font.labels=2, lwd=0.5)
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Re: [R-sig-eco] mrpp between pairs of factor levels
Cristabel, I don't know if this what you are after. Why don't you just use the subset of data you are interested in. mrpp(data=subset(spp, mhab == b mhab == nd), grouping=mhab, dist=bray, permutations=1000) or spp1 - subset(spp, mhab == b mhab == nd) spp1$mhab - factor(spp1$mhab) #to drop unused levels mrpp(data=spp1, grouping=mhab, dist=bray, permutations=1000) HTH Luciano 2010/9/24 cristabel.du...@waldbau.uni-freiburg.de Dear list, I'm performing a mrpp analysis for my data (spp), the grouping factor is mhab. mhab has five levels: b br c nd nongap t So, for a mrpp with factor mhab with all levels I'm doing: mrpp(data=spp, grouping=mhab, dist=bray, permutations=1000) BUT now I want is to perform a mrpp with only levels b and nd. I tried several ways without success: mrpp(data=spp, grouping=c(mhab==b nd) , dist=bray, permutations=1000) mrpp(data=spp, grouping=c(mhab==b mhab==nd) , dist=bray, permutations=1000) mrpp(data=spp, grouping=levels(which(envno34$mhab== b) which(envno34$mhab== b)), dist=bray, permutations=1000) I got this errors: - Error in x * w : non-numeric argument to binary operator - Error in levels(mhab(which(mhab == b) which(mhab == : attempt to apply non-function - Error in mhab == b nd : operations are possible only for numeric, logical or complex types ...etc...etc.. I think it should be possible to choose the factor levels which I want to work with, otherwise I should fix this issue from my species and environmental matrices. I appreciate your help! Thank you :-) Cristabel. Cristabel Durán Rangel. PhD Student. Institute of Silviculture. Faculty of Forest and Environmental Sciences. University of Freiburg. Germany Telf: +49 (761) 203 8604 (ofc) Man lernt die Physiognomie einer Landschaft desto besser kennen, je genauer man die einzelnen Züge auffaßt, sie untereinander vergleicht und so auf dem Wege der Analysis den Quellen der Genüsse nachgeht, die uns das große Naturgemälde bietet. Alexander von Humboldt, 1799 ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology [[alternative HTML version deleted]] ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
Re: [R-sig-eco] Function predict
Hi Manuel, your problem is that the new variables you created are of numeric type, while the model was fitted using factor. So the fix is to convert the new variables to factors so the type matchs Luciano 2010/7/7 Manuel Spínola mspinol...@gmail.com Dear list members, I am fitting a logistic regression with 5 explanatory factors (which I converted to factors): mod6 = glm(condicion ~ iluminacion + animales + cielo.raso + piso + paredes, family=binomial, data=reglog) I want to obtain the predicted probabilities and the se using the function predict for some combination of the factors. iluminacion = 1 animales = 0 cielo.raso = 0 piso = 0 paredes = 0 newdata1 = data.frame(iluminacion, animales, cielo.raso, piso, paredes) newdata1$cond = predict(mod6, newdata = newdata1, type=response) newdata1$cond = predict(mod6, newdata = newdata1, type=response) Aviso en model.frame.default(Terms, newdata, na.action = na.action, xlev = object$xlevels) : variable 'iluminacion' is not a factor Aviso en model.frame.default(Terms, newdata, na.action = na.action, xlev = object$xlevels) : variable 'animales' is not a factor Aviso en model.frame.default(Terms, newdata, na.action = na.action, xlev = object$xlevels) : variable 'cielo.raso' is not a factor Aviso en model.frame.default(Terms, newdata, na.action = na.action, xlev = object$xlevels) : variable 'piso' is not a factor Aviso en model.frame.default(Terms, newdata, na.action = na.action, xlev = object$xlevels) : variable 'paredes' is not a factor Error: variables 'iluminacion', 'animales', 'cielo.raso', 'piso', 'paredes' were specified with different types from the fit I don't understand what is wrong. Any help will be appreciated. Best, Manuel -- Manuel Spínola, Ph.D. Instituto Internacional en Conservación y Manejo de Vida Silvestre Universidad Nacional Apartado 1350-3000 Heredia COSTA RICA mspin...@una.ac.cr mspinol...@gmail.com Teléfono: (506) 2277-3598 Fax: (506) 2237-7036 ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology [[alternative HTML version deleted]] ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
Re: [R-sig-eco] Changing the reference level of a factor
Manuel, in order to save the changes you have to assign it to the data frame. Here is how you should do it. nidprop$treatment - relevel(nidprop$treatment, ref=c, data=nidprop) Luciano Selzer 2010/5/18 Manuel Spínola mspinol...@gmail.com Dear list members, I am trying to change the reference level of a factor but when I run a model with the lm function the new order it does not taking place (I still have the old order of the levels). relevel(nidprop$treatment, ref=c, data=nidprop) [1] a a a a b b b b c c c c Levels: c a b modelo1 = lm(hight ~ treatment, data = nidprop) summary(modelo1) Call: lm(formula = hight ~ treatment, data = nidprop) Residuals: Min 1Q Median 3Q Max -1.6052 -1.0626 -0.0950 0.9228 3.0768 Coefficients: Estimate Std. Error t value Pr(|t|) (Intercept) 37.9140 0.7368 51.461 1.98e-12 *** treatment[T.b] -0.2298 1.0419 -0.221 0.8304 treatment[T.c] -3.1133 1.0419 -2.988 0.0153 * --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 1.474 on 9 degrees of freedom Multiple R-squared: 0.552, Adjusted R-squared: 0.4525 F-statistic: 5.545 on 2 and 9 DF, p-value: 0.02696 Any idea why? Best, Manuel Spínola -- Manuel Spínola, Ph.D. Instituto Internacional en Conservación y Manejo de Vida Silvestre Universidad Nacional Apartado 1350-3000 Heredia COSTA RICA mspin...@una.ac.cr mspinol...@gmail.com Teléfono: (506) 2277-3598 Fax: (506) 2237-7036 ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology [[alternative HTML version deleted]] ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
Re: [R-sig-eco] nested mixed model?
Hi, I'm by no means an expert, just an PhD student. But in my humble opinion shouldn't you consider the individual effect? I think that the microtexture could be influenced by this. Luciano 2010/2/3 Mauricio Cifuentes mcifu...@gmail.com Hi everybody, I am trying to fit a model in R using the lme() function. I would like to have your opinion about what I did and if there are better ways to resolve this analysis. First Let me explain you how look the data that we are analyzing. We want to compare the tooth microtexture of four species of ungulates. For that we have taken pictures in eight different points within each tooth of one individual. We used as many teeth as were available for each individual taken in account their position and at the same time separating them by the place they were located (mandible: down tooth; maxilla: upper tooth). I am not an expert, but until here the model looks as nested design, please let me know if I am wrong. In summary we have the following hierarchy arrangement: Species (4 species) bone(mandible or maxilla) tooth points within each tooth (8 points). I have fitted this model using: lme(response ~ species, data=tooth, random=~1|bone/tooth/points,na.action=na.omit) I will be really grateful if you can give me your opinion about that. Best wishes Mauro ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology [[alternative HTML version deleted]] ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
