similar to: Bootstraping GAMs for confidence intervales calculation

Dear R-Users, I am trying to apply a bootstrap to a GAM in order to calculate the 95% confidence intervals for a smooth curve obtained by the ?plot.gam? function of the mgcv package. Nonetheless, I am getting some difficulties in transposing the results for the graphs. I used the following commands in R, ?mgcv? and ?boot? packages: *> attach(bbvc_11Jul08)* *>

Hi, I would like to add confidence intervales to an ANCOVA with 2 covariates when using xyplot. What would be a good way of accomplishing this? --8<---------------cut here---------------start------------->8--- rm(list = ls(all = TRUE)) rm(list = c(ls())) library(lattice) ## 1. generate data random <- rnorm(200) y <- abs(random) x1.cont <- abs(random) x2.fac <-

Thanks to the help of people from this forum I was able to bootstrap my data and then apply a model to it. Thanks for all your help. Everything worked out well, but I am having a difficult time getting the new parameter values. I bootstrapped the data 300 times and I want to get the 300 sets of parameter estimates and plot them in Excel. Here is my code:

Dear all, I have a standard method and two alternatives to perform a test, called method A and method B. I have calculated the sensitivity and specificity for standard method vs. method A and standard method vs. method B. Hence, I have two sensitivity values an two specificity values. To be clear, sensitivity and specificity was calculated from: Disease(A) No Disease(Ac) Total Positive

Hi I'm doing a bootstrap of a linear model using: boot.fishpower <- function(data, i){ data <- data[i,] fplm <- lm(log(U)~Q+S+P+B+D, data=data) fp <- coef(fplm) exp(fp) } > boot(logglm.data,boot.fishpower,100) Error in "[<-"(*tmp*, r, , value = statistic(data, i[r, ], ...)) : number of items to replace is not a multiple of replacement length

Dear R-friends, Unfortunately the tables that I "past" on last email gone with bad visual structure. So I send it again. Sorry to do this so confuse. Miltinho ==== Table1 - Bird records State,SampleSite,Species,Bodysize SaoPaulo,Site1,Spp01,4.39 SaoPaulo,Site1,Spp04,4.05 SaoPaulo,Site1,Spp01,2.75 SaoPaulo,Site1,Spp02,8.18 SaoPaulo,Site1,Spp02,0.80

Hi, Does anyone know what the error message mean? > Boot2.Pillai <- function(x, ind) { + x <- as.matrix(x[,2:ncol(x)]) + boot.x <- as.factor(x[ind, 1]) + boot.man <- manova(x ~ boot.x) + summary(manova(boot.man))[[4]][[3]] + } > > man.res <- manova(as.matrix(pl.nosite) ~ + as.factor(plankton.new[,1]))$residuals > boot2.plank <-

Hi. I''m learning AcriveRecord (I''m not building web apps for now, just playing with the database layer). Problem is, when I run the following code: require ''rubygems'' require ''activerecord'' puts ''hi'' It takes about 6 seconds. I''m using a slow computer. Now, it''s no fun playing when it takes so long to

I'm having trouble getting openldap through its initial setup. I created a /etc/openldap/slap.conf file with a default rootdn and rootpw, and they didn't seem to take effect. After much wailing and gnashing of teeth I found that if there is a config directory at /etc/openldap/slapd.d, it will ignore slapd.conf. I can't figure out how to translate slapd.conf into the (new?) standard

Hi everybody, I am sorry that I am kind of spamming this forum, but I have searched for some input everywhere and cant really find a nice solution for my problem. Data looks like: price 2011-11-01 08:00:00 0.000000000 2011-11-01 08:00:00 0.000000000 2011-11-01 08:02:00 0.000000000 2011-11-01 08:03:00 -0.017033339 2011-11-01 08:13:00 0.000690001 2011-11-01

Dear R-experts, I have a table with following collumns: State, SamplePlot, Species and BodySize. I sampled bird species at 34 SamplePlots and 5 States (regions) monthly during two years. On each bird record I measured bodysize and identified the species. So I have many records of each species (about 150 species) at each SamplePlot and each Region (State). Now I would like bootstrap

Hi List, I have start and end times of events structure(list(start = c("15:00", "15:00", "15:00", "11:00", "14:00", "14:00", "15:00", "12:00", "12:00", "12:00", "12:00", "12:00", "12:00", "12:00", "12:00", "12:00", "12:00",

Hi I have a plist t which contains size measurements of individual plants, identified by the field "plate". It contains, among other, a field "year" indicating the year in which the individual was measured and the "height". The number of measurements range from 1 to 4 measurements in different years. My problem is that I would need the LAST measurement. I only

Hello I recently switched from apcupsd to NUT2.2.2 without any troubles. I tried to figure out how I can configure the self-test intervall. The command upsrw lists only the variables battery.charge.low battery.runtime.low ups.delay.shutdown ups.delay.start The command usbhid-ups -D and the listing under http://obsvermes.org/cgi-bin/nut/upsstats.cgi?host=apcsmart at localhost&treemode

This command cdmoutcome<- glm(log(value)~factor(year) > +log(gdppcpppconst)+log(gdppcpppconstAII) > +log(co2eemisspc)+log(co2eemisspcAII) > +log(dist) > +fdiboth > +odapartnertohost > +corrupt > +log(infraindex) > +litrate > +africa >

OK, I have managed to use some of the basic processes of getting data from my DB, passing it as a whole to something like fitdistr, &c. I know I can implement most of what I need using a brute force algorithm based on a series of nested loops. I also know I can handle some of this logic in a brute force method using a blend of perl and R, with considerable file IO. But some of what I need

Dear list, I?m wondering if there is something analogous to the TukeyHSD function that could be used for parametric terms in a GAM. I?m using the mgcv package to fit models that have some continuous predictors (modeled as smooth terms) and a single categorical predictor. I would like to do post hoc test on the categorical predictor in the models where it is significant. Any suggestions?

Hi there, I was wondering if by the way the isotropic bivariate function works in the mgcv package, one can use highly correlated coordinates (given the shape of the study area) without worrying about the potential problems of correlation between explanatory variables, i.e., does s(LON, LAT) deal with that by considering their combined effect? Although this sounds more like a statistical

Dear list, I'm interested in fitting a generalized additive model in which some of the covariates are derived quantities and known measurement errors, and I am not sure how to incorporate the uncertainty of these covariates into the model fitting process. Could anyone point me towards relevant examples or documentation? Thanks in advance, Julian Julian M. Burgos Fisheries Acoustics

Hi I have been searching for goodness-of-fit tests (or lack of fit tests) for GAMs and cannot find anything. My problem is: after fitting a GAM to mortality data (smoothing crude estimated rates of mortality - a process called graduation in the actuarial literature), (1) how to assess the fit of the model with reference to "adherence to data" for the fitted model (I do not think the