search for: edf

...t, let's create some data to play around: set.seed(1) (df <- data.frame(Group=rep(c("Group1","Group2","Group3"), each=10), Value=c(rexp(10, 1), rexp(10, 4), rexp(10, 10)))[sample(1:30,30),]) ## Now we need the empirical distribution function: edf <- function(x) ecdf(x)(x) # empirical distribution function evaluated at x ## The big question is how one can apply the empirical distribution function to ## each subset of df determined by "Group", so how to apply it to Group1, then ## to Group2, and finally to Group3. You might sug...

...keep.list <- vector("list", steps) if (is.list(object) && (nmm <- match("nobs", names(object), 0)) > 0) n <- object[[nmm]] else n <- length(residuals(object)) fit <- object bAIC<- extractAIC(fit, scale, k = k, ...) edf <- bAIC[1L] #extracts the number of parameters, k=edf bAIC <- bAIC[2L]+((2*edf*(edf+1))/(n-edf-1)) if (is.na(bAIC)) stop("AICc is not defined for this model, so stepAIC cannot proceed") nm <- 1 Terms <- terms(fit) if (trace) { cat("St...

Hi folks BVT and EDF are both xen scheduler. It is expected that administrator will choose the scheduler most appropriate to their application and configure the machine to boot with that scheduler. I just wonder What''s the main difference between BVT and EDF? What kind of scenario to use them? Thanks ______...

Dear all I have found that the two "equivalent" commands do not produce the same results. 1. (I wrote this command by hand, this is what I would do usually) >summary(aov(eduyrs ~ cntry * edf, data=ESS1)) Df Sum Sq Mean Sq F value Pr(>F) cntry 1 257 256.65 21.2251 4.243e-06 *** edf 4 11010 2752.42 227.6296 < 2.2e-16 *** cntry:edf 4 24 6.03 0.4987 0.7367 Residuals 3205 38754 12.09...

...ot;identity")) extractAIC(G1) stepAIC(G1) extractAIC.glm <- function(fit, scale, k = 2, criteria = c("AIC", "AICc", "BIC"), ...) { criteria <- match.arg(arg=criteria, choice=c("AIC", "AICc", "BIC")) AIC <- fit$aic edf <- length(fit$coefficients) n <- nobs(fit, use.fallback = TRUE) if (criteria == "AICc") return(c(edf, AIC + (2*edf*(edf+1))/(n - edf -1))) if (criteria == "AIC") return(c(edf, AIC-2*edf + k*edf)) if (criteria == "BIC") return(c(edf, AIC -2*edf + lo...

Hello R experts I have two linear regressions for sexes (Male, Female, Unknown). All have a good correlation between body length (response variable) and head length (explanatory variable). I know it is not recommended, but for a good practical reason (the purpose of study is to find a single conversion factor from head length to body length), the regressions need to go through the origin (0

...nction" and "AIC () function". They are different. Then I just type "step" in the R console, and found the "AIC" used in "step() function" is "extractAIC". I went to the R help, and found: "The criterion used is AIC = - 2*log L + k * edf, where L is the likelihood and edf the equivalent degrees of freedom (i.e., the number of free parameters for usual parametric models) of fit. For linear models with unknown scale (i.e., for lm and aov), -2log L is computed from the deviance and uses a different additive constant to logLik and hen...

Hi, I've got the following edf: *** x = c(1.6,1.8,2.4,2.7,2.9,3.3,3.4,3.4,4,5.2) F2.5 <- ecdf(x) plot(F2.5, verticals= TRUE, do.p = TRUE, lwd=3, ylab = "", xlab = "", xlim = c(1,5.5)) abline(h= (0:5)*0.2) #mean abline(v=mean(x), lwd=2) mtext(text=expression(bar(x) == 3.07)...

Simon, in your recent reply to me, you noted that EDF=1 corresponds to a straight line fit. Does the edf always indicate the polynomial exponent directly? We ask because Hothorn and Everitt said "Roughly, the complexity of a cubic spline is about the same as a polynomial of degree one less than the degrees of freedom." Sorry we attribute...

...nd this was also the unix userid that I used to run the smbcontrol command so it has full unix authority. Smb.conf looks like this:- [global] workgroup = customer server string = csm1 SAMBA server interfaces = csm1 security = ADS realm = customer.edfenergy.net disable netbios = yes log file = /opt/pware64/var/sambalog log level = 1 max log size = 40960 name resolve order = host username map = /opt/pware64/lib/users.map create mask = 00 e.t.c...... Cheers, Steve North...

Hi! I''m currently working on Earliest Deadline First qdisc implementation for providing delay bounded real-time services according IntServ architecture under Linux. My first step was simple EDF implementation, that is available from http://www.avalon.ru/~dketov/. If someone interesting in using EDF or just trying and testing it, please go ahead :) Any questions are welcome. Dimitry. _______________________________________________ LARTC mailing list / LARTC@mailman.ds9a.nl http://mailman...

...low to enable a comparison. In addition, applying the default method="fREML" (mgcv version 1.7-17) on the same dataset yields only non-significant results, while all results are highly significant using method="REML". Furthermore, it also results in large negative (e.g., -8757) edf values linked to s(X,bs="RE") terms. Is this correct, or is this a bug? The summary of the model using method="fREML" is also shown below. I hope someone can shed some light on this. With kind regards, Martijn Wieling, University of Groningen #################################...

...me the function LogLik() seems to provide strange results regarding the number of degrees of freedom (df) for the gam, for instance in the example I copied below the df for the "gamm" are equal to the ones for the "lme", but the summary(model.gam) seems to indicate a much higher edf for the gamm. I would be very grateful to anybody who could point out a solution, Best wishes, Carlo Example below: ---- rm(list = ls()) library(mgcv) library(nlme) set.seed(123) x <- runif(100,1,10) # regressor b0 <- rep(rnorm(10,mean=1,sd=2),each=10) # random intercept id <-...

Dear R users, Would it be difficult to change the code of stepAIC (from the MASS library) to use AICc instead of AIC? It would be great to know of someone has tried this already. Best wishes Christoph.

...ciated. Regards, Mark Clements. (Apologies in advance for formatting etc. This is my first posting.) diff -ur c:/usr/temp/work/mgcv/R/mgcv.r ./R/mgcv.r --- c:/usr/temp/work/mgcv/R/mgcv.r 2002-05-17 03:04:26.000000000 +1000 +++ ./R/mgcv.r 2002-09-10 14:22:06.000000000 +1000 @@ -437,6 +437,7 @@ edf<-array(0,m) # estimated degrees of freedom ddiag<-array(0,3*m) # array for diagonostics idiag<-array(0,3) # array for diagnostics + hat<-array(0,n) # array for diagnostics Vp[1,1]<-1.0 M$gcv.ubre<-1.0; direct.mesh<-100 # number of points f...

...: gama1.3 <- gam(y~s(x, bs="cr")+z+int, family=quasipoisson) ##smooth the trend Model 4: gama1.4 <- gam(y~s(x, bs="cr")+z+s(int, bs="cr"), family=quasipoisson) ##smooth trend and interaction We have three questions. One question is simple. We occasionally obtain edf =1 and Ref.df=1 for some smoothed predictors (x, int). Because Wood says that edf can be interpreted roughly as functional form (quadratic, cubic etc) + 1, this would imply x^0 functional form for the predictor, and that doesn't make a lot of sense. Does such a result for edf and rdf indicate a...

...ains that both b and b1 fits are similar: "note that the preceding fit (here b) is the same as (b1)...." I agree with the idea that it "looks" the same but when I look at the results from both models (summary b and summary b1) I see that the results look in fact quite different (edf, and also deviance explained for example???) Are those two models (b and b1) really testing the same things??? If yes, why are the results so different between models??? Thanks a lot if anyone can help with that... Geraldine dat <- gamSim(4) ## fit model... b <- gam(y ~ fac+s(x2,by=fac)+s(...

...the following: ml1 <- mle(...) AIC(ml1) I get the following error messale: Error in logLik(object) : no applicable method for "logLik" Therefore I am using the following to calculate the AIC: #AICmle calculate AIC from mle object AICmle <- function( m, k=2) { lL <- logLik(m) edf <- attr(lL, "df") LL <- lL[1] - 2 * LL + k * edf } 1) Why is AIC not working with objects of class mle - am I doing something wrong, is it a bug or by design? 2) Just for confirmation - is my calculation of AIC correct? Thanks Rainer

...hese are basic questions. I am fitting some GAM models using the mgcv package and following the model selection criteria proposed by Wood and Augustin (2002, Ecol. Model. 157, p. 157-177). One criterion to decide if a term should be dropped from a model is if the estimated degrees of freedom (EDF) for the term are close to their lower limit. What would be the minimum number of EDF's for a) Univariate thin plate regression splines(TPRS) with shrinkage, i.e. s(...,bs="ts") b) Bivariate tensor products of TPRS with shrinkage? Thanks for any help, Julian Burgos -- Julian M...

...ault methods anyway), it becomes possible to make drop1() work with mer objects (Doug Bates's new mixed model code) merely by defining: terms.mer <- function(x, ...) { attr(x at frame,"terms") } extractAIC.default <- function(fit, scale=0, k=2, ...) { L <- logLik(fit) edf <- attr(L,"df") c(edf,-2*L+2*edf) } Adding this definition of extractAIC.default also makes drop1() work with lme fits ... Comments? Should I submit to the bug database as "enhancement request"? Are there any hidden downsides to this? Ben Bolker -------------- nex...