similar to: xyplot w/ panel.lmline "solution"

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

Dear All, Help is needed! I have a matrix with frequencies of fish larvae per length class (var. sl) and age-group (var. median.no) obtained with >k<-table(cut(sl,(5:22)),median.no) >k[2:5,1:5] #to ilustrate k 4 5 6 7 (6,7] 3 1 0 0 (7,8] 3 0 1 0 (8,9] 3 4 3 5 (9,10] 3 15 7 13 from this matrix I would like to obtain the mean age per length class i.e.

*Thanks* all those who took the time to help me (even if the "question" was not related to - the use of - R). Now I think I can soundly make my point w/ the referee (can I use your replies? If so I intend to properly cite its use?!?). Regards, Eduardo Esteves ps - Sorry for not explaining the "biological details" of my posting: RNA/DNA is the ratio of RNA content to

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,

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

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),

panel.lmline returns intercept and slope of y ~ x subsetted to the combination of conditioning factors given to xyplot in lattice. for instance: xyplot(Xvalues ~ log(Qvalues)|Tfac, data = df7, panel = panel.lmline) I am looking to find the equivalent formulation for lm() proper. If I do this: lmcal <- lm(Xvalues ~ log(Qvalues):Tfac, data = df7) Only one value of the intercept is returned.

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.

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

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

Hello r-list members, I've been doing some linear modeling with a dataset structured as follows. Tubes containing 500 larvae of Trichinella each were treated with one of four different temperatures. Each day (or every 10 days depending on treatment group), 3 tubes were selected from each treatment and all the dead larvae were counted. The tubes were discarded. Final larvae counts were

Dear All, I'me having (much) trouble understanding why it happened and answering a referee's comment to part of a submitted manuscript. I've tried to google for help but... I'm really confident that although this is a R-Help list someone can help me! I used R to do an ANCOVA w/ RNA/DNA as the dep var, sl as the indep var and gut (a factor w/ levels: prey and empty) as the

Dear all, How do I make R show the R-squared (deviance explained by the model) in a logistic regression? Below is how I write my syntax. Basically I want to investigate density-dependence in parasitism of larvae. Note that in the end I perform a F-test because the dispersion factor (residual deviance / residual df) is significantly higher than 1. But how do I make R show the

Dear all I have made some lattice graphs (bwplot(dead ~ treat | group,...). 'group' is a factor with three levels (Artemia larvae, Abalone larvae and Abalone spat), and the result is a graph with three panels corresponding to the levels in 'group', ordered in alphabetical order from bottom to top, as expected. How does one re-order the order in which the levels of

Dear All, I'm trying to calculate the following: g.rate<-(SL-int)/NO where SL and NO are individual length and counts for the same subject, and the int value is a day-specific value i.e. for each DAY=88, 101..., 172 I'd like to use a different values of int=9.32, 8.43, ..., 9.81. All variables are compiled in a larger data.frame of the form: CODE SL NO DAY (...) 123 12.5 14

1) I have a data that includes some "bad" data. I want to make a trellis plot where each panel contains a) A scatter plot of the "good" data b) A scatter plot of the "bad" data in a different color c) A best fit line of all the data, and d) A best fit line of the "good" data. I tried using xyplot and setting the "group" argument, but I'm

Background: OS: Linux Ubuntu Dapper R : Version 2.3.1 (2006-06-01) Emacs 21.4.1 ESS Colleagues This is neither a bug report, nor a complaint, so I think this is the appropriate list. I am getting an odd font problem with a pdf generated using pdf(file = "../figures/PCNM.models.larvae.fluor.zoo.stability.2001.and.2002.pdf", title="", family="serif",

Dear All, (this msg is a statistics/computing question to the list) I'm trying to implement a modern-version of a (classic) "several-step protocol" in Fishery Biology (due to Bhattacharya, 1967): analysis of length-frequency distribution of fish larvae to id cohorts and later estimate growh rates! I've trouble with the 1st step: using kernel density estimation (KDE) function

Dear All, A few weeks ago I posted a question to this list but unfortunately got no answer! A friend warned me of my english. Again, the problem is: A 2-level 5-factors completely randomized design was used to investigate the potential effects of those factors on a solution's characters (several response variables). Each response-variable was measured repeatedly (13 times) during a