search for: stackloss

Here is an example given from ?yags library(methods) data(stackloss) Y1 <- yags(stack.loss~Air.Flow,id=1:21, data=stackloss) How can I access parts of the output. I tried: > str(Y1) Formal class 'yagsResult' [package "yags"] with 25 slots ..@ coefficients : num [1:2] -44.13 1.02 ..@ coefnames : chr(0) > Y1$coefnames...

...[5] "fitted.values" "residuals" "scale" "terms" [9] "call" "xlevels" "model" Also is there any plotting available for lqs? And trying plot on the lqs object doesn't work: > data(stackloss) > set.seed(123) > examplelqs <- lqs(stack.loss ~ ., data = stackloss) > plot (examplelqs) Error in as.double.default(x) : (list) object cannot be coerced to vector type 14 thanks, --Clayton -- Clayton Springer, Ph. D. Sandia National Laboratories csprin at ca...

...instead of R-help. Then it would have been noticed by me and most probably several other R core members ... } > IMHO the reproducible code I presented in that post: > ############# > library(datasets) > alm <- lm(stack.loss ~ poly(Air.Flow, Water.Temp, degree=3), stackloss) > alm$fitted.values[1:10] # "correct" prediction values [1:10] > predict(alm, stackloss)[1:10] # gives correct values > predict(alm, stackloss[1:10,]) # gives wrong values > ######### > ... clearly demonstrates something wrong, the two predicts sho...

...why as.data.frame.default > kicks in erroneously. > > I'm still able to make progress with the S4 classes in R > with the RSMethods library, so I don't consider this too > urgent. > > vc > > # normal operations prior to library attachment > > > data(stackloss) > > stackloss[1:3,] > Air.Flow Water.Temp Acid.Conc. stack.loss > 1 80 27 89 42 > 2 80 27 88 37 > 3 75 25 90 37 > > # attach > > > library(RSMethods) > > Attaching...

Any help with this problem would be greatly appreciated: I need to produce a custom plot i haven't come across in R. Basically, I want to show means, 1st standard deviation and 5th and 95th percentiles visually, using something resembling a boxplot. Is it possible to completely customize a boxplot so that it shows means as the bar (instead of, not as well as medians), standard deviations at

Is there a way of getting a list of indices or something indicating which set of points lqs when doing a regression? The $bestone, seems to return only 2 pts. no matter how good or bad the fit. I checked the archive for the past few months, but didn't find anything. thanks in advance, Mark Hall -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help

Hi, I have been using the lqs function with method='lms'. However the results I get are a little different from the results noted by Rousseeuw & Leroy (Robust Regression and Outlier Detection) and I was wondering how to use these results for outlier detection. I'm using the stackloss dataset, for which the original Rousseeuw et al. program points out that observations 1,2,3,4 and 21 are outliers. This conslusion is arrived at by testing whether the residual is greater than 2.5 * standard error Netx I ran lqs as: m <- lqs(stackloss[,-4], stackloss[,4], method='lms'...

How do I add to a trellis plot the best fit line from a robust fit? I can use panel.lm to add a least squares fit, but there is no panel.rlm function. -- Alan S Barnett <asb at mail.nih.gov> NIMH/CBDB

Hello all, I'm using R2.7.0 (on Windows 2000) and I'm trying do run a robust regression on following model structure: model = "Y ~ x1*x2 / (x3 + x4 + x5 +x6)" where x1 and x2 are both factors (either 1 or 0) and x3.....x6 are numeric. The error code I get when running rlm(as.formula(model), data=daymean) is: error in rlm.default(x, y, weights, method = method, wt.method =

...quakes off Fiji randu Random Numbers from Congruential Generator RANDU rivers Lengths of Major North American Rivers rock Measurements on Petroleum Rock Samples sleep Student's Sleep Data stack.loss (stackloss) Brownlee's Stack Loss Plant Data stack.x (stackloss) Brownlee's Stack Loss Plant Data stackloss Brownlee's Stack Loss Plant Data state.abb (state) US State Facts and Figures state.area (state) US State Facts and Figures state.center...

Hello Can anyone tell me what I am doing wrong below? My Y and y_hat are the same. A<-scale(stackloss) n1<- dim(A)[1];n2<-dim(A)[2] X<-svd(A) Y<- matrix(A[,"stack.loss"],nrow=n1) Y y_hat <-matrix((X$u%*% t(X$u))%*%Y,nrow=n1,byrow=T) y_hat [[alternative HTML version deleted]]

...retrival at http://www.biostat.harvard.edu/~carey/cremo.html This package addresses the problem of assembling and rendering results of multiple linear model fits in formats suitable for presentation in applications contexts. An extract from the output of 'example(cremo)': cremo> data(stackloss) cremo> attach(stackloss) cremo> glm2 <- glm(stack.loss ~ Air.Flow + Water.Temp + Acid.Conc.) cremo> glm3 <- glm(stack.loss ~ Air.Flow + Water.Temp) cremo> glm4 <- glm(stack.loss ~ Air.Flow * Water.Temp) cremo> try(print(cremo(list(glm2, glm3, glm4), adeqel = c("de...

...============================================================== #mtrace(biplot.pca, T) #mtrace(biplot.pca, F) #??????????????????? # 2D with graphics package #??????????????????? #x = matrix(c(42, 52, 48, 58, 4, 5, 4, 3), nc=2); x #dimnames(x) = list(letters[1:nrow(x)], LETTERS[1:ncol(x)]); x #x = stackloss; x #x = cars; x #x = longley; x x = mtcars[,1:7]; x #x = LifeCycleSavings; x biplot.pca(x) biplot.pca(x, scale=T) biplot.pca(x, col.obj=3, col.var=4, var.red=.5) biplot.pca(x, center=T, scale=F, weight='eq', cex=.5) biplot.pca(x, center=T, scale=F, weight='eq', cex=.8) biplot.pca(x,...

...a nice LaTeX table for a rq object. Trying to use the functions I found so far wouldn't work. I can start opening the functions up, but I am wondering if I had missed some function which is the one I should be using. Here is an example session for a bunch of possible errors: (Thanks) data(stackloss) y <- stack.loss x <- stack.x rq_object <- rq(y ~ x, tau = .5) rq_object_summary <- summary(rq_object) latex(rq_object) # Error in UseMethod("latex") : # no applicable method for 'latex' applied to an object of class "rq" latex(rq_object_summary) # Error i...

...from the imputed one (removing > one independent variable at a time). I have tried to do the computations > by hand, but my figures do not match R's. That's essentially correct, but only if you mean removing one variable at a time and not replacing it. Here is an example: > data(stackloss) > fm <- lm(stack.loss ~ ., data=stackloss) > anova(fm) Analysis of Variance Table Response: stack.loss Df Sum Sq Mean Sq F value Pr(>F) Air.Flow 1 1750.12 1750.12 166.3707 3.309e-10 Water.Temp 1 130.32 130.32 12.3886 0.002629 Acid.Conc. 1 9.97 9.97 0.9...

...ons. > > Second, for examples of capability, there are too many exceptions in this instance. For example: > glm() can take a two-column matrix as a single response variable. > lm() can take a matrix as a response variable. > lm() can take a complete data frame as a predictor (see ?stackloss) > > None of these work naturally if everything is in a data frame, and some won?t work at all. > > Steve E > > > > > ******************************************************************* > This email and any attachments are confidential. Any use, copying or > d...

I am needing some expertise with regard to the S-Plus command lmRobMM and its R counterpart rlm(formula,data,method="MM") I have used lmRobMM(formula,data) in S-Plus on the Stackloss data and obtained for my residuals 6.217777 1.150717 6.427946 8.174019 -0.6713005 -1.248641 -0.4236203 0.5763797 -1.057899 0.3593823 11 12 13 14 15 16 17 18 19 20 0.9629239 0.4732042 -2.506497 -1.346176 1.344408 0.1432279 -...

On Sat, 15 Dec 2018, frederik at ofb.net wrote: > I agree with Steve and Achim that we should keep some examples with no > data frame. That's Objectively Simpler, whether or not it leads to > clutter in the wrong hands. As Steve points out, we have attach() > which is an excellent language feature - not to mention with(). Just for the record: Personally, I wouldn't recommend

...and prop.test() from Kurt Hornik. o New read.fwf(.) for reading fixed width format (KH). o New str(.) [alternative to summary(.) for programmers] (MM). o New example data sets "esoph", "infert" and "anscombe" (TL), "iris3" (KH) and "stackloss" (MM). o source(.) has several new arguments, notably ``echo = FALSE''. This is applied in the new function demo(.) which runs all the code in demos/ (but dynload). o strheight(.) is new, accompanying strwidth(.). Both now work for mathematical expressions (Paul Murre...

...and prop.test() from Kurt Hornik. o New read.fwf(.) for reading fixed width format (KH). o New str(.) [alternative to summary(.) for programmers] (MM). o New example data sets "esoph", "infert" and "anscombe" (TL), "iris3" (KH) and "stackloss" (MM). o source(.) has several new arguments, notably ``echo = FALSE''. This is applied in the new function demo(.) which runs all the code in demos/ (but dynload). o strheight(.) is new, accompanying strwidth(.). Both now work for mathematical expressions (Paul Murre...