similar to: 95% CI bands on a Lowess smoother

Hi, I'm doing anova on a matrix of multivariate data where I want to assess the effect of each column (element). My matrix is 86 rows x 31 columns. I've created a grouping factor of length 86 containing group assignments of 6 types. Then I run: x<- aov(matrix~grouping.factor) summary(aov.fit.raw, test="Wilks") This is working fine enough, but I'm getting different

Hello, I have a time-series of standards measured for Refractive index. They are daily standards, however, I didn't run one everyday so some days have no data. I can plot the values, but the x-axis does not represent the correct time series (i.e. it's just an evenly spaced 1,2,3 type axis). I want to plot the points with some form of representitive date line on the x-axis. I don't

Hi there, I know this is probably a really simple question, but without the correct keywords, or knowledge of the correct function it is hard to search for on the net or within R. How do I increment a dataframe (or similar) name within a loop and assign data? A simple example would be: for(i in 1:10){ test<-i } BUT I want it to be test[i] --- in other words I want my stored data to

Hello all, I'm dealing with geochemical analyses of some rocks. If I use the full composition (31 elements or variables), I can get reasonable separation of my 6 sources. Then when I go onto do LDA with the 6 groups, I get excellent separation. I feel like I should be reducing the variables to thos that are providing the most discrimination between the groups as this is important

Hey team, If I have a matrix: 1, 2, 3, 4, 4, 0, 1, 3, 0, 3 2 columns. I want to write an if command that looks at (in this case) row 3 and looks to see if either [3,1] or [3,2] has a zero in it. IF it does have a zero I want the zero to be placed in another matrix in the same position. I know how to do the latter part, I just can't get the if command to look at both cells and deal with

I have some data (REE plots - geochemistry) where I have values 1:14 for the x axis, but have no data for some x values. Here for example, let's say that I don't have data for x=2,5,8. So x<-1:14 y<-c(4, NA, 5, 9, NA, 3.4, 8, NA, 19, 22, 12, 14, 15.3, 15) if I plot the data plot(x,y) and then I want to join with lines lines(x,y) How do I get it so the points join across the

I have a vector: alleles.present<-c("D3", "D16", ... ) The alleles present changes given the case I'm dealing with - i.e. either all of the alleles I use for my calculations are present, or some of them. Depending on what alleles are present, I need to make matrices and do calculations on those alleles present and completely disregard any formula or other use of the

I've made an LDA model on some data from one source. I have some new data that I want to see if I can "place" to the sources in the LDA model. I used the predict function as follows: predict(wak.insitu.ld, wak.alr.alluvial) where wak.insitu.ld is an LDA model generated from some data and wak.alr.alluvial is new data of similar origin. When I look at the results, there is 86

Hi everyone, I have a PCA plot that I'm writing about in the text. There were so many symbols in different colours on it that I didn't include a legend in the plot as it would be useless. So what I was hoping to do was to talk about each set of replicates in the text and when I do that, use their coloured symbol in the text. So what I want to do is to get R to create some high quality

When I run a summary(anova) I get output for all of the elements (columns) as these are multiple - single anova results. Can I store the F values? I can't find the attribute of the fitted model attributes(fit) that stores these F values, and for that matter, P values. Thanks -- Gareth Campbell PhD Candidate The University of Auckland P +649 815 3670 M +6421 256 3511 E

Hello, What I am trying to do is: Generate a density plot of a population of data. This data has a bimodal distribution so I've isolated a couple of possible sub-populations and I want to overlay these two density plots over the first to see whether they are contributing to the bimodal population. I can do this fine with plot(density(...)) and lines(density(...)) . But the resulting plots

As I've mentioned a number of times. I find it very useful to have lowess() become a generic function so that a lowess.formula() can be defined. Below is a patch that makes both changes, as well as updating the corresponding help documentation. Gregory R. Warnes Manager, Non-Clinical Statistics Pfizer Global Research and Development Tel: 860-715-3536 ? DESCRIPTION ? Makefile ?

Colleagues ---------------------------------- System info: R version rw1022 on NT ESS v. 5.1.18 using emacs ver. 20.4 ---------------------------------- I would like to access the residuals from a lowess fit (function lowess() ) as an aid to assessing whether I am over-smoothing or under-smoothing a dataset (as in Cleveland's book "Visualizing data", section 3.3) Unless I

The lowess() help page refers to documentation in "src/appl/lowess.doc". This was moved to "src/library/stats/src/lowess.doc" in 2007. This patch fixes it: Index: src/library/stats/man/lowess.Rd =================================================================== --- src/library/stats/man/lowess.Rd (revision 79137) +++ src/library/stats/man/lowess.Rd (working copy) @@

Hi, A lowess method is defined in our package for one of our S4 classes. To explicitely define the generic this is being used if (!isGeneric("lowess")) setGeneric("lowess", useAsDefault = lowess) This works fine for many other methods inherited from various R packages. In this case a warning is issued in R CMD check: * checking R code for possible problems ... NOTE

hi: apologies for taking up everyone's time. my problem is probably documented somewhere, but I again cannot find it. (which reminds me: I cannot find a search engine that allows me to search the archives of this very useful mailing list.) * it seems that lines(lowess()) fails to plot certain line segments. (and, what does it do at the x-min and x-max of a data set?) Rather than

Hi, all, I want to use lowess(x, y) where x and y are vectors of length of 4000+. In fact, x and y are log of some vectors. So, some of the elements are NaN. lowess() can not take away those elements then do the fitting. It will give the error message and do nothing. 1. Can anybody tell me how to get rid of those NaN's and use lowess()? 2. How to get the LOWESS fitting values for any

Hi All, I've been providing a generic version of lowess() in my 'gregmisc' library, along with a 'lowess.formula' and 'lowess.default'. Can/should these be moved into base? -Greg LEGAL NOTICE Unless expressly stated otherwise, this message is confidential and may be privileged. It is intended for the addressee(s) only. Access to this E-mail by anyone else

Hi, I have a scatter plot of the variables GNI and Lifeexp (Gross National Income and Life Expectancy, both metric). So I plotted them and I want to add a regression line and a lowess line. I use lowess and not loess because I have missing values. My code: plot(GNI,Lifeexp) abline(lm(Lifeexp~GNI), col="red") y.loess<-loess(Lifeexp~GNI,na. action = na.exclude)

I am trying to change the attributes of the lowess lines fit to an xyplot command, but have been unsuccessful in my search of the online help. Right now, both the points and lowess line come out in the same color (blue). I am unsure how I can change the properties of the lowess line separately. xyplot ( SnowLineElevation ~ Year | Model, data = data, ylim = c(0,1800), type =