similar to: Is there an lm() equivalent of panel.lmline()?

Good day all, I'm trying to plot a continuous line plot, which is followed by two forecast points eg. one forecast point is 12 months out, and another 24 months out from the last date of the line plot. In my attempts so far, the second plot (the forecast points) is scaled against a new axis scale, thus the two plots are not directly comparable (I need the forecast points to be scaled

Dear all, Lets say I have several data frames as follows: > set.seed(42) > dates <- as.Date(c("2010-01-19", "2010-01-20")) > times <- c("09:30:00", "11:30:00", "13:30:00", "15:30:00") > shows <- c("Red Dwarf", "Being Human", "Doctor Who") > > df1 <- data.frame(Date = dates[1],

Hello, I have a nested named list structure, like the following: x <- list( list( list(df1,df2) list(df3, list(df4,df5)) list(df6,df7))) with df1...d7 as data frames. Every data frame is named. Is there a way to get a specific named element in x? so, for example, x[[c("df5")]] gives me the data frame 5? Thank you in advance! Best, Friedericksen

I am new to R. I want to graph group data using a "Traditional Bar Chart with Standard Error Bar", like the kind shown here: http://samiam.colorado.edu/~mcclella/ftep/twoGroups/twoGroupGraphs.html Is there a simple way to do this? So far, I have only figured out how to plot the bars using barplot. testdata <- scan(, list(group=0,xbar=0,se=0)) 400 0.36038 0.02154 200 0.35927

Hi R-users! I'm trying to create an easy Excel chart using the package RDCOMClient. The following example is working fine: #------------------------------------------------------------------- library(RDCOMClient) xlLocationAsObject <-2 xlXYScatterSmoothNoMarkers <- 73 ex <- COMCreate("Excel.Application") wb <- ex[["Workbooks"]]$Add() sh <-

Hi, I am trying to produce an xyplot with a regression line. The data should be represented as log/log but when I fit the lmline I receive an error message - the plot is fine without the log transformation, but the then the plot is meaningless. I know it must be something simple, but I just can't see it. Hope someone can help... Thanks. xyplot(log(Pk)~log(k),data=rwpk,cex=1,

Dear Sebastian Luque (and All R Users) With the following code I managed to plot different characters and regression lines for panels 2 ("Day of year 101") and >4 ("Days of year" 151, 157 and 172): xyplot(log(no.larvae)~age.cls|factor(day),data=mortal, layout=c(7,1),aspect=5/3, xlab="Age class (d)",ylab="Ln(Abundance)",

Dear All, I'm confortable with xyplot(...) and panel.lmline(...) statements (at least I thought I did :). I've used the following code to plot the decline in log-abundance of fish larvae (no.larvae) with age (age.cls, 4 to 27 days-old) for specific dates of sampling (day, 9 dates). I further plotted data with different colors and regression lines for ages 5-14 d and 17-23 d in a 7-by-1

Hi, is it possible to reverse the order in which panel.lmline() or panel.smooth() operation in xyplot() ? This type of situation might occur when plotting some variable with depth, but the relation we want to describe is variable ~ depth, and not depth ~ variable, as the plotting formula would suggest. # an example: d <- 1:100 v <- d * rnorm(100) xyplot(d ~ v, ylim=c(100,0),

I am wanting to generate panels showing scatterplots with the linear fitted line for two groups within each panel superimposed. I have two conditioning factors, "variable" and "Group" and I want separate panels for each level of "variable" with different symbols and "lmline"s for each level of "Group". However all observations for a group are

Dear All, I need to produce a multi-panel plot where: 1) groups within panels receive distinct symbols; 2) a linear regression is fit to the entire panel, not the individual groups; 3) a common abline is plotted in each panel. Essentially I would like to merge the two plots below, but I can't seem to figure out how to call both lmline and abline, and also retain the grouping symbols.

Hello, I'm using aov() to analyse changes in brain volume between males and females. For every subject (there are 331 in total) I have 8 volume measurements (4 different brain lobes and 2 different tissues (grey/white matter)). The data looks like this: Subject Sex Lobe Tissue Volume subect1 1 F g 262374 subect1 1 F w 173758 subect1 1 O g 67155 subect1 1 O w 30067 subect1 1 P g 117981

Hi R Folks... Are the results of a fit carried out by panel.lmline readily available for use in a lattice plot? I¹d like to put r^2, m, and b on each panel. I can certainly write something that does this manually and then use it with panel.text, but if it¹s already available, that would be preferable, especially as lattice permits condition and subsetting so readily. Looking at panel.abline, I

In the HistData package, I have a data frame, PearsonLee, containing observations on heights of parent and child, in weighted form: library(HistData) > str(PearsonLee) 'data.frame': 746 obs. of 6 variables: $ child : num 59.5 59.5 59.5 60.5 60.5 61.5 61.5 61.5 61.5 61.5 ... $ parent : num 62.5 63.5 64.5 62.5 66.5 59.5 60.5 62.5 63.5 64.5 ... $ frequency: num 0.5 0.5

Hi, I've just started using R and fdrtool, and I'm not sure if the qvalues I'm receiving back are accurate. I performed fdrtool on pvalues obtained from a two way anova on proteomics data. So I have 266 data values (protein spots) for two factors (ft, vr, and the interaction) for each biological sample. One of the two factors (vr) has a highly significant effect with 119 protein

On Friday 17 September 2004 13:52, RenE J.V. Bertin wrote: > Hello again, > > I am doing regressions (using panel.lmline() (and panel.abline( > rlm(...))) ) inside a panel method which I pass to bwplot(). > > What I would like to do is create a boxplot of categorised data > (binned on the independent variable), and superpose a regression line > which is calculated using the

R-Help community, I understand that data.frames can hold elements of type double, string etc but NOT objects (such as a matrix etc). This is not convenient for me in the following situation. I have a function that takes 2 inputs and returns a vector: testfun <- function (x,y) seq(x,y,1) I have a data.frame defined as follows: testframe<-data.frame(xvalues=c(2,3),yvalues=c(4,5)) I would

Dear All: I have succeeded in fitting a GAMLSS.dist model to growth data I am working with it. My aim is to create a matrix of predicted percentiles and the corresponding the fitted model's sigma mu nu by agebins. Q: How do it generate these parameters as in L M S per Cole and Green 1992? Here are my working codes. Name of fitted model is gamlssfit > Agebin<-seq(6,36,6)

Hola, Esta es una forma de hacerlo... Mira que lo primero que he modificado es el fichero "x.csv" para sustituir los espacios en los nombres por "_". Y también he quitado los acentos y las eñes... He utilizado el paquete RNNS y la función "mlp()" para ajustar la red. #------------------------------------------- > x <- read.csv("x.csv",

Hello all, I would like to do a Dunnett test in glht(). However, the factor level I want to use as the control is not the first. dunn1<-glht(model3, linfct = mcp(Container = "Dunnett"), alternative = "less") The factor container has 8 levels, so it would be nice not to manually enter in all of the contrasts. I originally discovered glht() when working with a glm model