search for: girth

Yes, I am a newbie at R, but it is not the complex commands in R that have me baffled, but simple data commands. For example, why does something like: > plot(Girth ~ Height) *not* work after a command that allegedly loads the data: > data(trees) with the error message: Error in eval(expr, envir, enclos) : Object "Girth" not found but does work after the command: > attach(trees) ? - JRV -- There are 10 kinds of people: those who unde...

...FROM flashings GROUP BY flashings.code; Here is a sample of the records. select * from flashing_codes limit 10; code | description | folds ----------+------------------------------------------+--------------------- SG.05A | ALUMINIUM FLASHING C/B GIRTH 520MM FOLDS | {1,0,2,3,4,5,6} DN.03Z | .6MM FLASHING Z/A GIRTH 200MM FOLDS | {0,6,5,4,3,2,1} SR.05G | .6MM FLASHING GAL GIRTH 300MM FOLDS | {5,4,3,2,1,0,6} RR.06Z | .6MM FLASHING Z/A GIRTH 400MM FOLDS | {6,5,4,3,2,1,0} RR.05G | .6MM FLASHING GAL GIRTH 300MM FOLDS...

I am trying to run an ancova and am having trouble setting it up properly. I have nearly 10,000 measurements of fish length, girth and stage of sexual development. I am suspicious that the stage of development is affecting the length (as they get full of eggs they get more round and are more difficult to measure and measure shorter). My data looks somethign like this: Length girth stage 40 50 2 42 48 3 37 40 5 38...

...2:4) print(update(Harman23.FA, factors = factors)) Call: factanal(factors = factors, covmat = Harman23.cor) Uniquenesses: height arm.span forearm lower.leg weight 0.170 0.107 0.166 0.199 0.089 bitro.diameter chest.girth chest.width 0.364 0.416 0.537 Loadings: Factor1 Factor2 height 0.865 0.287 arm.span 0.927 0.181 forearm 0.895 0.179 lower.leg 0.859 0.252 weight 0.233 0.925 bitro.diameter 0.194 0.774 chest.gir...

...which is needed to predict results. But, as soon as I set a value for this option, the whole model generation fails. Check this example: ------------------------- library(caret) tc=trainControl(method='LGOCV', timingSamps=10) tcWithout=trainControl(method='LGOCV') x=train(Volume~Girth+Height, method="lm", data=trees, trControl=tcWithout) x=train(Volume~Girth+Height, method="lm", data=trees, trControl=tc) Error in eval(expr, envir, enclos) : object 'Girth' not found Timing stopped at: 0 0 0.003 ---------------------------- As you can see, the model g...

...foreach_1.4.0 cluster_1.14.2 reshape_0.8.4 [6] plyr_1.7.1 lattice_0.20-6 loaded via a namespace (and not attached): [1] codetools_0.2-8 compiler_2.15.0 grid_2.15.0 iterators_1.0.6 [5] tools_2.15.0 ------- Simlified Testcase I: Throws warning --- library(caret) data(trees) formula=Volume~Girth+Height train(formula, data=trees, method='rpart') --- Simlified Testcase II: Every other CV-method also throws the warning, for example using 'cv': --- library(caret) data(trees) formula=Volume~Girth+Height tc=trainControl(method='cv') train(formula, data=trees, method=...

Hi all, I'm an R newbie, I did this script to create a scatterplot using the "tree" matrix from "datasets" package: library('datasets') with(trees, { plot(Height, Volume, pch=3, xlab="Height", ylab="Volume") symbols(Height, Volume, circles=Girth/12, fg="grey", inches=FALSE, add=FALSE) } ) I'd like to use the column Named "Height" to fill the circles with colors (ex.: the small numbers in green then yellow and the high numbers in red). I'd like to have a legend for the size and the colors too. I did it manually...

Dear all, I would like to get glm() return its results (at least the deviance) for some given parameter values (ie without actually fitting the model). I tried to set `maxit = 0' but this does not work, eg: > glm(y ~ x, start = c(1, 1), maxit = 0) Error in glm.control(...) : maximum number of iterations must be > 0 Any idea? Thanks in advance. Emmanuel Paradis

Hi Everyone, I often use the 'safe prediction' feature available through glm(). Now, I'm at a situation where I must use biglm:::bigglm. ## begin example library(splines) library(biglm) ff <- log(Volume)~ns(log(Girth), df=5) fit.glm <- glm(ff, data=trees) fit.biglm <- bigglm(ff, data=trees) predict(fit.glm, newdata=data.frame(Girth=2:5)) ## -1.3161465 -0.2975659 0.4251285 0.9856938 predict(fit.biglm, newdata=data.frame(Girth=2:5)) ## Error in predict(fit.biglm, newdata = data.frame(Girth = 2:5)) : ##...

...ibility of customizing the degree for the 'lm' method. This might be due to the fact that the basic 'lm' function does not support the degree parameter. I tried the following solution using a different formula for the second training: ----- library(caret) data(trees) formula=Volume~Girth+Height degFormula=Volume~(Girth+Height)^2 m1 = train(formula, data=trees, method="lm") m2 = train(degFormula, data=trees, method="lm") ------- The problem with this solution is that the 'extractPrediction' method of R does not work if comparing models with different for...

...5 data(trees) s3d <- scatterplot3d(trees, type="h", highlight.3d=TRUE, angle=55, scale.y=0.7, pch=16, main="scatterplot3d - 5") # Now adding a regression plane to the "scatterplot3d" attach(trees) my.lm <- lm(Volume ~ Girth + Height) s3d$plane3d(my.lm, lty.box = "solid") [[alternative HTML version deleted]]

...eneral purpose model plotting function "plotmo" may also be useful to people who are not interested in earth itself. Example: > a <- earth(Volume ~ ., data = trees) > summary(a, digits = 2) Call: earth(formula = Volume ~ ., data = trees) Expression: 23 + 5.7 * pmax(0, Girth - 13) - 2.9 * pmax(0, 13 - Girth) + 0.72 * pmax(0, Height - 76) Number of cases: 31 Selected 4 of 5 terms, and 2 of 2 predictors Number of terms at each degree of interaction: 1 3 (additive model) GCV: 11 RSS: 213 GRSq: 0.96 RSq: 0.97 Regards, Stephen Milborrow _______________...

...tupid question... I have a large dataset that is to big for my computer memory, and I found quite useful the package biglm. Now everything is working perfectly. But if I want the residuals, how I can do it? Let's say that we are running the example: > data(trees)> ff<-log(Volume)~log(Girth)+log(Height)> > chunk1<-trees[1:10,]> chunk2<-trees[11:20,]> chunk3<-trees[21:31,]> > a <- biglm(ff,chunk1)> a <- update(a,chunk2)> a <- update(a,chunk3)> > summary(a)Large data regression model: biglm(ff, chunk1)Sample size = 31 Coef...

...eneral purpose model plotting function "plotmo" may also be useful to people who are not interested in earth itself. Example: > a <- earth(Volume ~ ., data = trees) > summary(a, digits = 2) Call: earth(formula = Volume ~ ., data = trees) Expression: 23 + 5.7 * pmax(0, Girth - 13) - 2.9 * pmax(0, 13 - Girth) + 0.72 * pmax(0, Height - 76) Number of cases: 31 Selected 4 of 5 terms, and 2 of 2 predictors Number of terms at each degree of interaction: 1 3 (additive model) GCV: 11 RSS: 213 GRSq: 0.96 RSq: 0.97 Regards, Stephen Milborrow _______________...

...an error on the part that plots the regression plane: > library(scatterplot3d) > data(trees) > s3d <- scatterplot3d(trees, type = "h", color = "blue", + angle = 55, scale.y = 0.7, pch = 16, main = "Adding elements") > my.lm <- lm(trees$Volume ~ trees$Girth + trees$Height) > s3d$plain3d(my.lm) Error: attempt to apply non-function > s3d$points3d(seq(10, 20, 2), seq(85, 60, -5), seq(60, 10, -10), + col = "red", type = "h", pch = 8) Any ideas on what I need to change in order to get the plane to plot? Tom -- View this me...

...for volume) whether a three is thick. If my interpretation is correct, for low trees, i.e. for which trees$isHigh == FALSE, the answer is yes. The problem is how to "merge" the standard errors. Code follows. data(trees) trees$isHigh <- trees$Height > 76 trees$isThick <- trees$Girth > 13 m <- lm(trees$Volume ~ trees$isHigh + trees$isThick + trees$isHigh:trees$isThick) summary(m) I might be mistaken, but a workaround is to rewrite the model as follows, which shows that the answer is yes. However, I would very much like to know how to answer the question with the original...

How does one turn a character string back into an object? I would like to take character strings and use them as objects, a process that I think is the reverse of deparse( substitute(X)). E.g., I would like to get the variable names from the fourth object listed with objects(), something like names(objects()[4]), but of course that doesn't work. Thanks Henry Dr. M. Henry H. Stevens

I am attempting to fit a logistic regression plane to a 3-D scatterplot (which was generated using scatterplot3d). I've noticed that the help pages of scatterplot3d include a function titled "plane3d." However, when I attempt to use the function, I get the following message: Error: couldn't find function "plane3d" I've searched the archives and found no

...n after I saw this example (it is from uwe ligges book): install.packages("scatterplot3d") library("scatterplot3d") data(trees) s3d <- scatterplot3d(trees, type = "h", angle = 55, scale.y = 0.7, pch = 16, main = "trees") my.lm <- with(trees, lm(Volume ~ Girth + Height) ) s3d$plane3d(my.lm, lty.box = "solid" ) Normally I just have to group the ranges which show the km in 10000 blocks and group the points as well, but I didn't come that far. even the scatterplot3d funtion didn't work for my data (gwx and x is my data table). 仩x <- gw...

I was trying to produced bagged importance estimates of attributes in earth using the caret package with the following commands:   fit2 <- bagEarth(loyalty ~ ., data=model1, B = 10)   bagImpGCV <- varImp(fit2,value="gcv") My bootstrap estimates are produced however the second command "varImp" produces the following error:    Error in UseMethod("varImp") : no