similar to: corCompSymm in gamm()?

Hi, I am new to R. How can I get labels/different colours on the lines in my xy-plots. I plot "het" against "temp" conditional on "year" and "station". library(lattice) MyLines <- function(xi, yi, ...){ #Draws line in the panels while avoiding spaghetti-plots I <- order(xi) panel.lines(xi[I], yi[I], col = 1)} xyplot(het ~ temp | fstation,

Hi, I have had some troubles using doubleYScale. No matter what I try, I cant manage to change the color of the y-axis in the end. I have to produce a black and white plot. There is also something I do not understand regarding fontfamilyj="serif" when using it in: strip=strip.custom() Maybe someone has a better idea for defining which line and dots belong to which y-axis when not using

Hi, I am attempting to correct my models p-values due to temporal autocorrelations. It is not possible to model the correlation, so I have to make do with the p-value correction. I am feeling a bit thick here....I cannot get the autocorrelation values. What is the argument? My aim is to multiply the dependent variable autocorrelation with the independent variable autocorrelation and then

Hi, I have used the mgcv library to generate a simple additive model. I want to know how to plot the function on the raw data with confidence intervals whan I have TWO variables in the model. I get it to work with one variable but not with two. I am on the limit for what I understand in R, so be gentle. I have read the help file on predict.gam, but did not get any help out of it. #My model:

Dear R-devel members, While writing a new correlation structure similar to 'corCompSymm' and intended to be used with 'gnls', I got puzzled with the 'Initialize' method. Using 'Initialize' before 'gnls' may be regarded as a mean to set an initial value for the corStruct parameter. However 'gnls' does not work properly with a

We are trying to use the corCompSymm function in nlme The example from the help pages for the corAR1 function gives the following > corAR1(0.2, form = ~ 1 | Mare) Correlation structure of class corAR1 representing Phi 0.2 We are expecting a somewhat similar correlation specification with the help page example for corCompSymm, but just get an error instead > corCompSymm(0.5, form = ~ 1 |

Dear R Friends, I need help with an error associated with corCompSymm in an lme fit. I am using a mixed effects model to analyze a split-plot with repeated measures and would like to fit with the compound symmetry correlation structure. This problem doesn't occur when using corAR1 or any of the other structures. I would greatly appreciate help on how to solve this issue. Here's my

Hi, I know that according to plot theory, one should not have two y-axis. It is just that in my field, we are often depending on plots where water depth is plotted in one y-axis and other parameters such as salinity on the other y-axis to see where the halocline (the depth where the two layers of water are not mixed) is located. I have many other examples. To publish, it is required of me to

Hi lattice users, I would like to add 5-year moving averages to my double y-plot. I have three factors needs to be plotted with moving averages in the same plot. One of these reads off y-axis 1 and two from y-axis 2. I have tried to use the rollmean function from the zoo-packages, but I fail in insering this into lattice (I am not an experienced lattice user). I want to keep the data points in

Dear group, I am trying to use gamm() in mgcv. Here's the scenario. The data frame has approx. 110K observations with information on paediatric readmission binary outcome (Y/N) and total volume of their most responsible physician as the covariate. Since any physician can have multiple patients, the data contains clustering structure which I am trying to account for. My original formula is

Hi, Dummy data script and scripts are attached below. I would like to change the plot to look like this:

Hi, I have a data set with two continous variables that I want to plot MEANS (I am not intrerested in median values) on a double-y graph. I also have 2 factors. I want the factor combinations plotted in different panes. Dummy dataset: mydata <- data.frame(factor1 = factor(rep(LETTERS[1:3], each = 40)), factor2 = factor(rep(c(1:4), each = 10)), y1 =

Hi everyone (again), before you all start screaming that the reordering of factors has been discusse on several threads and is not particular to ggplot2, hear me out. I can easily reorder my x-axis factor in facet.grid() in ggplot2. What I cannot reorder are the factors represented on the strips. I can see that the graphs are changing, so I am afraid of what it is I am doing. Why is ggplot2

Hi there, I have relative abundance data for 13 mammal species that I collected at various sites that ranged in road density. I'm trying to determine the effect of road density on animal abundance across body sizes. For most species, I have data that was collected in one year but for a few species I have two years of complete data, and would like to use both. Since I have count data, I'm

Following the setup in Prof.Duncan Murdoch's page, I have successfully compiled the DLL for one Fortran 95 program using Gfortran and got 300 times speed boost. For the second set of fortran programs, However, I have this error message R CMD SHLIB -o jiangang kdtree2.f90 jian.f90 gang.f90 m2c -o jian.o jian.mod make: m2c: Command not found make: *** [jian.o] Error 127 Can anyone

Dear R users, I have now tried out several options of obtaining p-values for (quasi)poisson lmer models, including Markov-chain Monte Carlo sampling and single-term deletions with subsequent chi-square tests (although I am aware that the latter may be problematic). However, I encountered several problems that can be classified as (1) the quasipoisson lmer model does not give p-values when

dear R wizards:? I am wrestling with reshape.? I have a long data set that I want to convert into a wide data set, in which rows are firms and columns are years. > summary(rin) firm fyear sim1 Min. :1004.00 Min. :1964.0 Min. : -1.00000 1st Qu.:1010.00 1st Qu.:1979.0 1st Qu.: -0.14334 Median :1016.00 Median :1986.0 Median : 0.00116 Mean

Dear Friends, I am seeking for any help on an error message in lme functions. I use mixed model to analyze a data with compound symmetric correlation structure. But I get an error message: "Error in corMatrix.corCompSymm(object) : NA/NaN/Inf in foreign function call (arg 1)". If I change the correlation structure to corAR1, then no error. I have no clue how to solve this problem.

Hi, I want to plot means with standard deviations of Total Nitrogen (TN) across 4 stations (S1-S4) and over 3 years (2007-2009). I want this plot in one panel. I do not want medians (bwplot, boxplot). I have tried a few different packages and it seems that ggplots with plotmeans was the fastest (I am not extremely skilled in writing my own scripts). Unfortunately, there is no grouping

Hi, # For publications, I am not allowed to repeat the axes. I have tried to remove the axes using: # yaxt="n", but it did not work. I have not understood how to do this in ggplot2. Can you help me? # I also do not want loads of space between the graphs (see below script with Dummy Data). # If I could make it look like the examples on the (nice) examples page: #