similar to: Trouble with 'smooth' using xyplot in lattice

Suppose that I'm working on Hadley's diamond dataset and I want to review the relationship between price, colour and carat. I might run the following: library(ggplot2) #plot scatter and add some hex binning q<-qplot(carat,price,data=diamonds, geom=c("hex"), main="Variability of Diamond Prices by Carat and Colour") #facet to get one scatter for

Hello, I have been using scatter.smooth and been trying to format my plots and been unable to adjust the line type or color of the smooth curve. When I specify col in scatter.smooth, I can adjust the color of the scatter plot points, but the line always stays black and solid. lty has no effect. When I specify par prior to calling scatter.smooth, col will change the color of the points,

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

Hello everybody, I'm trying to understand how to draw a smoothed scatterplot on a geographic map with R. Have a dataframe with point locations (long, lat) and was able to simply plot these points on a shp map by using the maptools package. However, instead of having simply the raw points on the map, I would like to have a "smoothed" scatterplot of the same superimposed on the map.

Dear R Users, I am looking for a smoothing function with the following characteristics for a time series of data: - at each date, should only use data up to that date (so, right aligned and not centered) - should return a smoothed series of length equal to the original time series: - for a one-day time series, just returns that day - this means the front part of the series will

Hi r-sers, I have a data of relative frequencies for the interval of 0-20, 20-40,...380-400.  I would like the two data on the same graph using the same x-axis label.  My question is how to get a smooth curve using kernel density code if it possible for this data.   > cbind(rel_obs,rel_gen)           rel_obs rel_gen  [1,] 0.000000000  0.0000  [2,] 0.092534175  0.0712  [3,] 0.105152471  0.1092

I am using the R code listed below to create 4 smoothed lines on a xyplot. I'm having trouble fine tuning it. First I think I may need a black and white plot so how do I get it to plot the lines with different characters, preferable the same characters used in the key (plus, X circle and triangle). I might also be interest in a version that draws four solid lines of different colors but

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 would like to draw smooth curves instead of polygons. I could not find any spline function to do that : given an x and a y vectors, they all take the x in increasing order. Is there a function to draw a smooth curve through a set of points in any order ? with many thanks in advance Alain Guerreau CNRS Paris [[alternate HTML version deleted]]

Hi, The following call: xyplot(incidence ~ year, melanoma, panel=panel.smooth) produces a blank plot region with an error message: Error using packet 1 plot.new has not been called yet > sessionInfo() R version 2.11.1 (2010-05-31) x86_64-pc-linux-gnu locale: [1] LC_CTYPE=en_CA.UTF-8 LC_NUMERIC=C LC_TIME=en_CA.UTF-8 LC_COLLATE=en_CA.UTF-8 LC_MONETARY=C

Hello users, I would like to obtain a survival curve from a Cox model that is smooth and does not have zero differences due to no events for those particular days. I have: > sum((diff(surv))==0) [1] 18 So you can see 18 days where the survival curve did not drop due to no events. Is there a way to ask survfit to fit a nice spline for the survival?? Note: I tried survreg and it did not

Hi, 1) I have noticed that when I use the aggregate function it outputs numbers in the results. for example: aggregate by product group.1 Aggregate 1 ProductA 1000400.00 2 ProductB 23232323.00 3 Missing 232323.00 is there a way to suppress the numbers infront of aggregate outputs. I checked and they don't look like columns when I do a summary so I can't -1

I have 3 sets of Cartesian data, one is 'original' data and the other 2 are "smoothed"data. The smoothed data is the result of applying a smoothing algorithm to the original.One set of smoothed data is the 'old' algorithm and the other set is the 'new' algorithm. Does R have the capability of telling me which data is "smoother"? Example data (subsets

Hi, I have some queries that I use to get time series information for 8 seperate queries which deal with a different set of time series each. I take my queries run them and save the output as csv file and them format the data into graphs in excel. I wanted to know if there is an elegant and clean way to read in 1 csv file but to read the seperate matrices on different rows into seperate

Hi all, I'm trying to draw a contour plot with rounded (smoothed) contour lines instead of sharp angles; when the grid consists of only a few points in x- and y- axis, the resulting contour is in facts rather ugly since very sharp angles may appear. I did not find any way to do it, by using either "contour" or "contourplot" (from the lattice package), I wonder if there

Dear All, I am using xyplot() with many groups like this: statselect <- levels(dat$stat) xyplot(relmse~T|lambda, groups=stat, data=dat, panel = panel.superpose, key=simpleKey(statselect, lines=T)) However, I want lines not scatterplots and if I set panel.groups=panel.linejoin that connects the lines according to the relmse and not according the consecutive values of T. Is there

I have a problem regarding the colors assigned to the lines in the key to an xy plot. I specify the plot like this: xyplot(numbers~sqrt(breaks)|moltype+disttype, groups = type, data = alldata, layout = c(3,2), type = "l" , lwd = 2, col = c("gray", "skyblue"), key = simpleKey(levels(alldata$type), points = FALSE, lines = TRUE, columns = 2, lwd = 2,

DeaR list, I'm trying to represent some information via 3D plots. My data and session info are at the end of this message. So far, I have tried scatterplot3d (scatterplot3d), persp3d (rgl), persp (graphics) and scatter3d (Rmcdr) but any of them gave me what I'd like to have as final result (please see [1] for a similar 3D plot changing PF by ypred, pdn by h4 and pup by h11). In general

I have used smooth.ppp in spatstat to create a smoothed surface plot based on randomly selected depths across a lake (as marks). I wonder if based on the smoothed surface plot if I can calculate the average depth for each 10x10 grid square across the lake. I can't see any obvious way of doing this and would appreciate some pointers. Many thanks, Graham [[alternative HTML version

Please help me to produce smoothed contour plots. I have dependent data generated at regular intervals of two independent variables and would like to produce smoothed contour plots - I cannot get interp (alima) to produce cubic interpolations of the data, only linear ones. I'm interested in smoothing as the data generation process is stochastic and produces small variations which I'd