similar to: Interpreting Q-Q Plots

I have a reshaped data frame with value column headings concatenated from two column headings in the melted data frame. I want to change all 56 headings in a single command, but 'names' allows me to change only one at a time. In Hadley's 2007 article on reshape in the Journal of Statistical Software he mentions a 'rename' function, but I cannot find that. Is there a way to

One of many scripts to produce 4 lattice plots on one page keeps throwing an error. I've tried manipulating the file to eliminate the error, but have not been able to do so. The error is: > source('bicarb.R') Error in source("bicarb.R") : bicarb.R:15:1: unexpected symbol 14: 15: hco33 ^ The 'h' is in column 0 so the caret would be column -1, but it's

I have a data frame called chemdata with this structure: > str(chemdata) 'data.frame': 14886 obs. of 4 variables: $ site : Factor w/ 148 levels "BC-0.5","BC-1",..: 104 145 126 115 114 128 124 2 3 3 ... $ sampdate: Date, format: "1996-12-27" "1996-08-22" ... $ param : Factor w/ 8 levels "As","Ca","Cl",..:

I need to understand how and why dcast() adds NAs to a data frame that contained no missing values. The database table of chemical concentrations has all missing values removed because they cannot contribute to data analyses. The structure of the R data frame of these data have no NA values, and neither does the data frame resulting from applying the reshape2 melt() function to it. However,

With multiple panels in a lattice trellis plot the sequence is, for example, 1, 10, 11, 12, 2, 3, 4. I want the sequence to be 1, 2, 3, 4, 10, 11, 12. Reading ?strip.default and the appropriate section in the Lattice book I'm not seeing how to specify the 'human' numeric order rather than the computer numeric order. A pointer will be appreciated. TIA, Rich

The bio.infer package contains a data frame /usr/lib/R/library/bio.infer/data/itis.ttable.rda that needs to be modified. After loading the bio.infer package and attaching the data frame with the data() function, I wrote the data frame to a text file. After adding another row to the data frame I applied read.table() to create a data frame, but it's in my pwd, not the R library data

Data frame has this structure: 'data.frame': 11169 obs. of 4 variables: $ stream : Factor w/ 37 levels "Burns","CIL",..: 1 1 1 1 1 1 1 1 1 1 ... $ sampdate: Date, format: "1987-07-23" "1987-09-17" ... $ param : Factor w/ 8 levels "As","Ca","Cl",..: 1 1 1 1 1 1 1 1 1 1 ... $ quant : num 0.01 0.01 0.01 0.01

Hi Albrecht, I am forwarding your reply to the full group. It's been a while since I did this and I don't remember the details. Maybe someone else can comment. (I am a bit busy at the moment.) If no one supplies the information in a few days I will try to take a look. In the meantime you can start your reading on-line. :-) Regards, Eric Dear Eric, I downloaded the material from

I read in ?na.omit that it returns the object with incomplete cases removed. I interpret this to mean that any zoo object row where any column shows 'NA' will be removed from the data set. That's not what I need, since the 'NA' represents information in my context. However, what I would like to do is eliminate the rows where every column is 'NA'. When I aggregate

I'm brand new to Samba and I am trying to set in up on our network (linux OS). We have two windows clients: a notebook running win95 (soon to be win98) and a virtual machine running win98. Right now, the host is running RH 5.2 with the 2.0.36 kernel. Samba-2.04b was installed from the rpm. I'm using Carter and Sharpe's "Teach Yourself Samba in 24 Hours" as my guide. On

I have water chemistry data with censored values (i.e., those less than reporting levels) in a data frame with a narrow (i.e., database table) format. The structure is: $ site : Factor w/ 64 levels "D-1","D-2","D-3",..: 1 1 1 1 1 1 1 1 ... $ sampdate: Date, format: "2007-12-12" "2007-12-12" ... $ preeq0 : logi TRUE TRUE TRUE TRUE TRUE

Hello R user, I have a data set from a longitudinal study ( sample below) where subjects are followed over time. Second column (status) contains info about if subject is dead or still in the study and third column is time measured in the week. Here is what I need: if status is not dead or unknown take the last week, if status is dead or unknown I need to have corresponding week. Desired resulst:

I've looked at the lattice book and the 'R Graphics Cookbook' without seeing how to change the labels along the x axis for groups in a box plot, specifically cenbox(). The attached example has a main and axes labels with default group labels. Please point me to a reference on how I can change 'FALSE' and 'TRUE' to something more easily understood by viewers. TIA,

I've looked again at Deepayan Sakar's 'Lattice' book and not seeing the information I know must be in there. A clue stick would be much appreciated. A pair of box-and-whisker plots for two conditions of the same data set display each box plot horizontally (see attached pH figure). Relations of the two are not as easily seen as they would be if the two panels had the plots

Because of regulatory requirement changes over several decades and weather conditions preventing site access the variables in my data set have different lengths. I'd like guidance on how to perform linear regressions and other models with these variables. For example, there are 2206 rows for the parameter "TDS" but only 1191 rows for the parameter "Cond." Such

I don't see what's missing in my statements to add rows to a data frame and someone else will probably see what needs to be added to the statements. The data frame has this structure (without any data): $ PHYLUM : chr $ SUBPHYLUM : chr $ SUPERCLASS : chr $ CLASS : chr $ SUBCLASS : chr $ INFRACLASS : chr $ SUPERORDER : chr $ ORDER : chr $ SUBORDER :

I would appreciate pointers on what I should read to understand this output: summary(lm(TDS ~ Cond + Ca + Cl + Mg + Na + SO4)) Call: lm(formula = TDS ~ Cond + Ca + Cl + Mg + Na + SO4) Residuals: ALL 1 residuals are 0: no residual degrees of freedom! Coefficients: (6 not defined because of singularities) Estimate Std. Error t value Pr(>|t|) (Intercept) 125 NA

I have installed Suse on an IBM as400 (powerpcc). This is SuSe 8.0 gcc 3.2 and with both samba 3.0.0 and 3.0.1pre3 I get this error message on the compile. (configure runs fine. make Using FLAGS = -g -O2 -I./popt -Iinclude -I/home/rshepard/samba-3.0.0/source/include -I/home/rshepard/samba-3.0.0/source/ubiqx -I/home/rshepard/samba-3.0.0/source/smbwrapper -I. -D_LARGEFILE64_SOURCE

R-3.5.0 is installed here. When I tried to update installed packages errors were reported when their dependencies were built under a prior version of R. Reading ?update.packages() I did not see an option that would automatically update dependences built under an earlier version of R. Is there such an option that I missed? Alternatively, is there a function I can run that will rebuild all

One set of data has censored (less-than detection limits) water chemistry concentrations for 80-100% of all observations. My initial trial-and-error attempts to apply the cenboxplot() method suggests that it has an upper limit to the percentage of censored observations. I do not see this limit in Dennis Helsel's second edition. Has anyone experience plotting censored data and can provide