search for: vcv

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2012 Oct 27
0
[gam] [mgcv] Question in integrating a eiker-white "sandwich" VCV estimator into GAM
...t, I don't get the graphs, which I want. 2. In the graphs given by plot(gam.object), I get confidence intervals that correspond to standard errors that are NOT based on the sandwich estimator, above. How could I get GAM to plot confidence intervals based on the sandwich estimator for the vcv matrix? 3. Some of the terms are interactions. (i.e.: T*var2). I realize that GAM has tensor product capabilities, but (1) frankly I don't understand them yet, and (2) I want my semi-parametric fit to be comparable to polynomial "parametric" fits. So, in addition to the plots...
2009 Oct 19
1
Defining S3-methods for S4-objects: cannot coerce type 'S4' to vector of type 'integer'
...(fm1, c(1,1)) Confidence interval ( WALD ) level = 0.95 beta0 Estimate Std.Error X2.value DF Pr(>|X^2|) Lower.CI Upper.CI 1 0 261.8724 6.786701 1488.888 1 0 248.5707 275.1741 The problem above arises because esticon.mer() uses the variance-covariance matrix of the fixed effects (vcv below) in a calculation (cm is a matrix): cm %*% vcv %*% t(cm). The result is: 1 x 1 Matrix of class "dgeMatrix" [,1] [1,] 46.05931 - and taking diag() of that matrix causes the error above... However, things work fine if I use as.matrix() as is: diag(as.matrix(cm %*% vcv %*%...
2001 Dec 06
2
Contrasts in lm
Dear all, In SAS (GLM and MIXED) estimable functions (linear functions of the parameters) can be specified in the ESTIMATE and CONTRAST statements. Has anyone written a similar "utility" for use in connection with lm? Thanks in advance S?ren H?jsgaard -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read
2009 Sep 06
1
Concentration ellipsoid
Hi all, Can anyone please guide me how to draw a Concentration ellipsoid for a bivariate system with a bivariate normal dist. having a VCV matrix : Sigma <- matrix(c(1,2,2,5), 2, 2) I would like to draw in using GGPLOT. Your help will be highly appreciated. Thanks, -- View this message in context: http://www.nabble.com/Concentration-ellipsoid-tp25315705p25315705.html Sent from the R help mailing list archive at Nabble.com.
2013 Mar 06
1
Difficulty in caper: Error in phy$node.label[which(newNb > 0) - Ntip]
...ding required package: MASS Loading required package: mvtnorm > > mammaldata <-read.csv("R.Mammal_data.csv", header = TRUE) > mammaltree <-read.nexus("BEphylotree.nex") > mammal <- comparative.data(phy = mammaltree, data = mammaldata, names.col = Taxon, vcv = TRUE, na.omit = FALSE, warn.dropped = TRUE) #names.col? Error in phy$node.label[which(newNb > 0) - Ntip] : only 0's may be mixed with negative subscripts -- Nicole A Thompson E3B Columbia University, NYCEP nat2103 at columbia.edu 480.522.4212
2012 Nov 29
1
[mgcv][gam] Manually defining my own knots?
...y~s(x,k=3),knots=list(dumb.knots)) plot(dumb.example) dumb.example2 = gam(y~s(x,k=3)) plot(dumb.example2) Dumb example 1 is the same as dumb example 2, but it shouldn't be. Once I figure out how to do this, I'll take the fitted coefficients from each model and average them, then take the vcv's from each model and average them, and add a correction to account for within and between imputation variability, then plug them into a gamObject$coeffient and gamObject$Vp matrix, plot/summarize, and have my result. Comments welcome on whether or not this would be somehow incorrect would...
2006 May 10
1
ape comparative analysis query
I've been comparing variables among objects (taxa) related by known trees, using phylogentically independent contrasts in the ape package, and want to move on to more complex models e.g. by using gls with appropriate correlation terms. My trees contain lots of (hard) polytomies and information about ancestors, which I've been including- creating fully dichotomous trees by using zero branch
2013 Jan 28
2
Why are the number of coefficients varying? [mgcv][gam]
...tiple imputation framework -- specifying the knot locations, and saving the results of multiple models, each of which is fit with slightly different data (because some of it is predicted when missing). In MI, coefficients from multiple models are averaged, as are variance-covariance matrices. VCV's get an additional correction to account for how variable they are between each other. For this to work in the context of a penalized spline model, the knots need to be specified identically for each model (this is assisted by context knowledge), and each model needs to have the same numbe...
2011 Aug 04
0
phyres function in caper package
...title of the message etc... Sorry.## I am running following phylogenetic analyses with the caper package: data=read.table(file="data.txt",header=T,sep="\t") tree = read.nexus("Tree.nex") primate = comparative.data(phy=tree, data=data,              names.col=Species, vcv=TRUE, na.omit=FALSE, warn.dropped=TRUE) PGLM_brain=pgls(ln_brain~ln_body,data=primate, lambda="ML")     summary(PGLM_brain) Now I would like the get the phylogenetic residuals of this model, which I should be able to do with the phyres function: resbrain=phyres(PGLM_brain) But then I...
2012 Jun 18
0
Obtaining r-squared values from phylogenetic autoregression in ape
...quot;, "PH", "R", "SB","SC", "SPBF", "SPW", "SS", "SSB", "SSS", "SW", "SWF", "WB", "WLH", "WW") > names(data) <- species > cor.mat <- vcv.phylo(treeX, cor=TRUE) > regr <- compar.cheverud(data, cor.mat) > regr$rhohat [1] 5.541462 > 1 - var(regr$residuals)/var(data) [,1] [1,] -1.333095 I don't understand why the autoregression coefficient falls outside the interval -1 to 1, or why the calculation for obtai...
2008 May 09
1
Which gls models to use?
Hi, I need to correct for ar(1) behavior of my residuals of my model. I noticed that there are multiple gls models in R. I am wondering if anyone has experience in choosing between gls models. For example, how should one decide whether to use lm.gls in MASS, or gls in nlme for correcting ar(1)? Does anyone have a preference? Any advice is appreciated! Thanks, -- Tom [[alternative HTML