similar to: NEWBIE: Help explaining use of lm()?

When I combine separate vectors into one list, there are new names created. I'd like to change them to something more meaningful. Here are two examples using data(zelazo) from library(ISwR): > library(ISwR) > data(zelazo) > attach(zelazo) > zelazo $active [1] 9.00 9.50 9.75 10.00 13.00 9.50 $passive [1] 11.00 10.00 10.00 11.75 10.50 15.00 $none [1] 11.50 12.00 9.00

Hello all, A really noddy question for you all: I''m trying without success to do some subhypothesis testing. Using simple anova model, with a toy dataset from a book. I have four factors A,B,C,D, and wish to test mu_C = mu_D. This is what I have tried: > contrasts(infants$group,how.many=1) <- c(0,0,1,-1) > contrasts(infants$group) [,1] A 0 B 0 C 1

Dear R users, Inspired by previous list discussion of the glob2rxc function, I am attempting to create a new vector called TOTAL by summing all vectors whose names begin with ABC: TOTAL = sum(list = ls(pattern = glob2rx("ABC*"))) I'm running R 2.2.1 on Windows XP. Can anyone say what I'm missing? Thank you, Mark

Passing in two dates to a sql statement (sqldf). Is returning a factor. Tried setting back to a Date via as.Date, but get an error the error: character string is not in a standard unambiguous format. Any thoughts appreciated. Code/Results listed below: > summary(df.possible.combos) Date Hour Min. :2011-03-01 Min. : 0.00 1st Qu.:2011-03-23 1st Qu.: 5.75

All of our Kafka clusters are fairly write-heavy. The cluster in question is our second-heaviest ? we haven?t yet upgraded the heaviest, due to the issues we?ve been experiencing in this one. Here is an iostat example from a host within the same cluster, but without the RAID check running: [root at r2k1 ~] # iostat -xdmc 1 10 Linux 3.10.0-327.13.1.el7.x86_64 (r2k1) 05/27/16 _x86_64_ (32 CPU)

If I use latex(summary(X)) where X is a data frame with four variables I get something like Rainfall Education Popden Nonwhite Min. :10.00 Min. : 9.00 Min. :1441 Min. : 0.80 1st Qu.:32.75 1st Qu.:10.40 1st Qu.:3104 1st Qu.: 4.95 Median :38.00 Median :11.05 Median :3567 Median :10.40 Mean :37.37 Mean :10.97 Mean :3866

I am puzzled at the use of regression. I have a categorical variable ClassePop33000 which factors a Population variable into 3 levels. I want to investigate whether that categorical variable has some relation with my dependent variable, so I go : lm(Cout.ton ~ ClassePop33000, data=ech2) Call: lm(formula = Cout.ton ~ ClassePop33000, data = ech2) Residuals: Min 1Q Median 3Q

Hi, I have a dataset with many observations some days while only one others. I would like to calculate a mean value per day and then do regression analysis on the means. This is what I have: Year Day Time herring.density 2007 47 10.36 2.2 2007 47 11.50 1.1 2007 47 14.24 1.4 2007 66 9.35 2.5 This is what I want:

Hello, I'm cc'ing R-Help. Sorry but your question was asked 3.5 years ago, I really don't remember it. Can you please post a question to R-Help, with a reproducible example that describes your problem? Rui Barradas ? Citando catalin roibu <catalinroibu at gmail.com>: > Dear Rui, > ? > I helped me some time ago with a code..... regarding aggregated data >

Dear list member, My question is related to input file format to an Anova from car package. Here is an example of what I did: My file format is like this (and I dislike the idea that I will need to recode it): Hormone day Block Treatment Plant Diameter High N.Leaves SH 23 1 1 1 3.19 25.3 2 SH 23 1 1 2 3.42 5.5 1 SH 23 1 2 1 2.19 5.2 2 SH 23 1 2 2 2.17 7.6 2 CH 23 1 1 1 3.64 6.5 2 CH 23 1 1 2

Dear R experts, beginners and everyone else, I'm calculating "cumulative periodogram" using the command "cpgram" [1] from the MASS library. Here is a short example with the "lh" (hormone level) dataset: library(MASS) plot(lh,type="l",ylab="value",xlab="time", main="Hormone Levels (lh)") spectrum(lh,

Dear all, I am trying to analyze data from an experiment like this: Factors: Hormone - Levels: SH, CH (S = without; C=with; H=Hormone) Time - Levels: 19/08/09, 04/09/09, 18/09/09, 08/10/09, 20/10/09 (DD/MM/YY) Nutrition - Levels: Completa, Sem (without) Macronutrition - Levels: Ca, K, Mg, P, Sem (without) Time is the measures day. It reflect the days after germination. Blocks : 4 plants per

Hi, This is not an R question, but I've seen opinions given on non R topics, so I wanted to give it a try. :) How would one treat a variable that was measured once, but is known to fluctuate a lot? For example, I want to include a hormone in my regression as an explanatory variable. However, this hormone varies in its levels throughout a day. Nevertheless, its levels differ substantially

Often, when exploring a dataset, I'd like to plot several very different Y variables against the same X variable, in panels stacked one over the other. Is there an easy way to do this? I'd like to achieve an elegant look similar to the look achieved by lattice in conditioned plots--for instance no space between panels. But unlike in straightforward conditioned plot, each panel may be on a

Dear list, havig the following matrix "Value" "Class" 13.00 1 12.80 1 11.78 1 11.70 2 11.61 2 11.95 2 11.55 2 12.40 3 11.40 1 12.27 1 12.49 3 11.39 4 11.80 4 12.39 3 12.72 3 12.18 3 11.64 3 11.50 4 12.81 4 11.31 4 11.95 2 12.65 2 11.66 2 12.19 3 12.84 1 11.90 1 11.11 4 12.75 4 how can I

Hi, I'm a new R user, coming from SPSS, and without a particularly strong stats background. I've got a data set that I'd like to do a mixed-design ANOVA with. No missing values. Here's the summary: summary(learnDat.ae) Type Subject idio struct TrainErrs cond 0:20 11 : 3 idio :28 ae :58 Min. : 0.00 idioae :28 2:19 12 : 3

I did some additional testing - I stopped Kafka on the host, and kicked off a disk check, and it ran at the expected speed overnight. I started kafka this morning, and the raid check's speed immediately dropped down to ~2000K/Sec. I then enabled the write-back cache on the drives (hdparm -W1 /dev/sd*). The raid check is now running between 100000K/Sec and 200000K/Sec, and has been for several

Current dragonegg svn has all of the -fplugin-arg-dragonegg-enable-gcc-optzns bugs for usage with -ffast-math -O3 addressed except for those related to PR2314. Using the -fno-tree-vectorize option, we can evaluate the current state of -fplugin-arg-dragonegg-enable-gcc-optzns with the Polyhedron 2005 benchmarks compared to stock dragonegg and stock gcc 4.5.4. The runtime benchmarks below show that

Dear R users, I want to aggregate all *d *data from all combination of n *plots* taken by k. Thank very much! My data is like that: plot d 1 14 1 13 1 12 1 14 1 18 1 20 1 21 1 43 1 108 1 43 2 41 2 61 2 83 2 61 2 84 2 45 2 21 2 12 2 11 ... 100 10 100 12 -- --- Catalin-Constantin ROIBU Forestry engineer, PhD Forestry Faculty of Suceava

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