search for: grp

...m is also that I want to extend it from a single variable case to a multivariable case and haven't really got a clue how to go about it. Hope someone can help. # The code below creates a data.frame comprising two marginally noisy straight lines and performs a # regression on each based on the grp factor. This is a single variable case based on R wiki one liner. # y = x for grp A # y = 2 + 5x for grp B set.seed(5) ind <- as.vector(runif(50)) d1 <- data.frame(x=ind, y=ind + rnorm(50,0,0.1), grp=rep("A", 50)) d2 <- data.frame(x=ind, y=2+5*ind+rnorm(50,0,0.1), grp=rep("...

Dear Spencer and Prof. Fox, Thank you for your replies. I'll very appreciate, if you have any ideas concerning the problem described below. First, I'd like to describe the model in brief. In general I consider a model with three equations. First one is for annual GRP growth - in general it looks like: 1) GRP growth per capita = G(investment, migration, initial GRP per capita, spatial lag on GRP growth + some additional explanatory variables to control for regional disparities), where spatial lag on GRP growth in year t is simply spatial weights matrix...

...ffects. Following previous correspondence . Dataset <- read.table("C:/Program Files/R/rw2011/data/miss/model1a.dat", header=TRUE, sep="\t", na.strings="NA", dec=".", strip.white=TRUE) attach(Dataset) require (nlme) with(Dataset, table(runnb, id, grp)) b.lvls <- table(Dataset$runnb) nb <- length(b.lvls) fit <- vector(mode="list", nb) for(i in 1:nb) fit[[i]]<- lme (trans1 ~ Index1 + grp, random = ~ 1 | id / grp , data = Dataset, na.action = "na.exclude")...

...my modifications noted. x <- fossil$age y <- 100000*fossil$strontium.ratio knots <- seq(94,121,length=25) n <- length(x) X <- cbind(rep(1,n),x) Z <- outer(x,knots,"-") Z <- Z*(Z>0) # I had to create the groupedData object with one group to fit the model I wanted grp <- rep(1,n) grp.dat<-groupedData(y~Z|grp) fit <- lme(y~-1+X,random=pdIdent(~-1+Z),data=grp.dat) I would like to know how I could fit this same model using the lmer function. Specifically can I specify a Z matrix in the same way as I do above in lme? Thanks, Mark

...have now done. The code below creates a data.frame comprising three marginally noisy surfaces. The code below (including a fix courtesy of David Winsemius that avoids a step function error through use of the "by" function) returns significant coefficients for regressions based on factor grp. In the case of grp A the intercept is not significantly different from zero. However I can't get step to consider dropping the intercept term. In the attached code the returned function for grp A is y ~ x1+x2. However I think it should return y ~ -1 + x1 +x2 (or I guess y ~ 0 + x1 + x2). If I...

On F7, I get to where I have Postfix and Dovecot installed and configured, postfix check runs fine, but when I try to start Dovecot I'm getting a permission error. Here is the log entry: Dec 29 21:54:06 grp-01-50-90 dovecot: Dovecot v1.0.7 starting up Dec 29 21:54:06 grp-01-50-90 dovecot: Generating Diffie-Hellman parameters for the first time. This may take a while.. Dec 29 21:54:06 grp-01-50-90 dovecot: auth(default): bind(/var/run/dovecot/auth-master) failed: Permission denied Dec 29 21:54:06 grp-0...

...or the three groups (each group represented by a different symbol), overlaid by the fitted regression lines for each group's relation between the 'x1' and 'y' variables, covarying the remaining four 'x' variables and adjusting them to their mean values. #All five of the grp*x interactions are significant in: fit1=lm(log(y)~grp*(log(x1)+log(x2)+log(x3)+log(x4)+log(x5)) summary(fit1) #However, to avoid sending all of the data, I create dummy data-sets #that have distributions resembling the original variables (which are #very skewed, hence the log-transformations). gr...

...s looking at them know how to view those estimates. I am successfully able to do this in a straightforward set of steps. However, once I place those steps inside a function it fails. Here's the code (sorry this is a long post): # create data wt <- rgamma(6065, 0.7057511981, 0.0005502062) grp <- sample(c(replicate(315, "Group1"), replicate(3672, "Group2"), replicate(1080, "Group3"), replicate(998, "Group4"))) dta <- data.frame(grp, wt) head(dta) str(dta) # declare design my.svy <- svydesign(ids=~1, weights=~wt, data=dta) # subset grp1 &...

...e size for every group in a bwplot as a parenthetical annotation to the axis. Here's a sketch: --8<---------------cut here---------------start------------->8--- require(Hmisc) age <- sample(1:100, 1000, replace = TRUE) sex <- gl(2, 8, 1000, c("Male", "Female")) grp <- gl(4, 6, 1000, letters[1:4]) bwplot(grp ~ age | sex, aspect = 0.5, box.ratio = 2, panel = function(x, y, ...) { panel.bpplot(x, y, nout = 0.01, probs = seq(0.05, 0.45, 0.05)) nage <- tapply(age, grp, length) panel.text(rep(0, length(x)), seq(along = x), l...

Although this should be trivial, I'm having a spot of trouble. I want to make a lattice plot of the format y1+y2 ~ x | grp but then fit a lm to each y variable and add an abline of those models in different colors. If the xyplot followed y~x|grp I would write a panel function as below, but I'm unsure of how to do that with y1 and y2 without reshaping the data before hand. Thoughts appreciated. -Andy foo <- da...

...the dots indicates a Z value (like e.g. earthquake maps where dot sizes indicate magnitudes and X/Y the location). This works fine with xyplot, e.g.: xyplot(1:3~1:3,cex=1:3,pch=16) However, when I do this with a panel variable, e.g.: x<-rep(1:3,5) y <- rep(1:3,5) sz <- rep(1:5,each=3) grp <- factor(rep(1:5,each=3)) xyplot(y~x | grp , cex=sz) then sz in the cex argument is not applied per group as I would expect. Same for other arguments like col. Is this really the intended behaviour? How can I achieve what I want, i.e., that the cex argument is different for the different...

...package. My first attempt was to try doing a t-test in lme. This is very similar to the Rail example that comes with nlme, but it has two groups instead of five. So I try a1 <- 1:10 a2 <- 7:16 t.test(a2,a1) getting t(18)=4.43, p=.0003224. Then I try to do it with lme: a12 <- c(a1,a2) grp <- factor(rep(1:2,c(10,10))) Now, at this point, I think I should be able to do something like this: lme(a12~grp) or lme(a12~1|grp) but I keep getting an error message, "Invalid formula for groups." So I tried making a groupedData object: data1 <- as.data.frame(cbind(a12,grp)) gd...

All I want to overlay two variables on the same plot following their appropriate grouping. I have attempted to use subscripting in panel with panel.xyplot, but I can't get the grouping to follow into the panel...here is an example... dat<-data.frame( y= log(1:10), y2=10:19, x=1:10, grp = as.factor(1) ) dat2<-data.frame( y= log(10:19), y2= 20:29, x=1:10, grp = as.factor(c(2)) ) dat<-rbind(dat, dat2) # Here I plot both response variables on y axis by the same x xyplot(y2 ~ x, dat, groups=grp, type="l") xyplot(y ~ x, dat, groups=grp, type="l") # I wan...

Hello, Just did a fresh install of xen-4.0 and using the 2.6.31.13 dom0 kernel. I have 6 linux debian guests running, and on my host console i am getting these errors rolling pretty constantly. "Attempting to checksum a non-TCP/UDP packet, dropping a protocol 1 packet" I tried doing the ethtool -K eth0 tx off and same thing on peth0, using bridged mode for network config. Any tips?

Hello, Just did a fresh install of xen-4.0 and using the 2.6.31.13 dom0 kernel. I have 6 linux debian guests running, and on my host console i am getting these errors rolling pretty constantly. "Attempting to checksum a non-TCP/UDP packet, dropping a protocol 1 packet" I tried doing the ethtool -K eth0 tx off and same thing on peth0, using bridged mode for network config. Any tips?

Hi, I try to ask here, because I hope someone will help me understand this problem- I have fittet a glm in R with the results > glm1 <- > glm(log(claims)~log(sum)*as.factor(grp),family=gaussian(link="identity")) > summary(glm1) Call: glm(formula = log(claims) ~ log(sum) * as.factor(grp), family = gaussian(link = "identity")) Deviance Residuals: Min 1Q Median 3Q Max -6.6836 -1.3626 -0.2576 1.2038 8.2480 Coefficien...

..., 0.663383934998686)), .Names = c("g10", "l1", "d1", "l13", "d13" ), row.names = c(1L, 2L, 3L, 1758L, 1759L, 1760L), class = "data.frame") ----------- If some one doesn't want to open github - here is the code ## Doesn't work # grp -- name of a column of the the data.frame df # function call is -- getMinMax1( df1 , grp = "var1") getMinMax1 <-function(df, grp){ dfret <- ddply( df , .(as.name(grp)), ## I am using as.name(grp), source of error function(x){ minmax <- c(mix(x[...

Hi I am trying to add a less than equal sign to a plot. I have previously done this using unicode but is not working in this instance. Any suggestions would be great thanks example code: library(ggplot2) df<-data.frame(vis=c(0,0,1,1) , count=c(10,15,20,10) , grp=c(0,1,0,1)) df$grp <-factor(df$grp ,levels=c(0,1) , labels =c("x \u2265 10" , "x > 10")) ggplot(df, aes(x = factor(vis), y=count , fill=grp)) + geom_bar(stat = "identity") -- View this message in context: http://r.789695.n4.nabble.com/ggplot2-less-than-equal...

Dear all, I am looking for a function to count values belonging to a class within a dataframe (and ignore NAs). grp = c(1,1,1, 1,2, 2,2) val = c(2,1,5,NA,3,NA,1) dta = data.frame(grp=grp, val=val) The result should look like: grp count 1 3 2 2 At the moment, I am trying to find a function for FUN in aggregate, but with no success. Can anybody help me? Thanks in advance. Marcus

...? Variable text acet = "Acetylaspartate Thalamus" chol = "Choline Thalamus" acetp = "Acetylaspartate parieoc" ino = "Inositole Thalamus" I could not find a solution. Please have a look at my syntax. Thanks a lot, Udo library(lattice) grp <-c(0,1,0,1) zp <- c(1,1,2,2) acet <- c(1.7,1.8,1.9,1.8) chol <- c(0.6, 0.8,0.8, 0.7) ino <- c(0.6, 0.3, 0.5, 0.4) acetp <- c(1.8, 1.9, 2.0, 1.8) data <- data.frame(cbind(grp, zp, acet, chol, ino, acetp)) data$grp <- factor(data$grp) levels(data$grp) <- c("low"...