similar to: lm() notation question

I was cursing Matlab again today (what else is new) because the default action for every Matlab command is to spew the result to the console, and one must remember to put that darn ";" at the end of every line. So I just wondered: was there ever a discussion as to providing some modified version of the "<-" and "->" operators in R to do the reverse?

Hi Say I want to add manually an intercept in the function lm. Even if almost all results will be identical, few stats are different as DF counting will be different as intercept will not be included in "automatic" case, while it will be in "manual" case. See: ###usual lm on freeny fr<-lm(freeny.y~freeny.x) ###manual lm on freeny man<-cbind(1,freeny.x)

Hi My goal is to do a (multiple) regression, just knowing that my Y variables will be the say k first variables of a matrix/data frame. I thought I should do it with eval(parse)) but encounter a strange problem. See: lm(y~.-y, data=freeny) #that's what I want to do in the one equation case #Problem is I don't know name of the variable... only that it is the first one... #so idea is to

Hello! I would love to be able to include an external variable to a lm call, I mean something: if(TRUE) a<-freeny.x[,4] else a<-NULL lm(freeny.y~freeny.x[,-4] +a) but it does not work with a<-NULL, whereas lm(freeny.y~freeny.x[,-4] +NULL) I don't understand why and did not find an answer in the manuals... do you see it? Any idea? Thanks!!

Hi, Here's the problem I ran into: the gmp package has a method for apply() so it masks the base::apply function. With gmp installed, I tried to run the function turnpoints() from the pastecs package. It fails because it calls apply() internally, like this: apply(mymatrix,1,max,na.rm=TRUE) , but the code in the gmp package which sets up the operator overload for apply() strictly

Hi I have a few problems with tail/head when applied to multiple time series. I'm not sure as whether I did not understand the function or whether it correspond to an unexpected behavior. When head(a,n) is applied on data.frame or matrix, it returns a data-frame or matrix with first n obs of *each* variable. When applied to a mts object, it returns first n obs of *first* variable only,

Full thread here: https://github.com/tidyverse/broom/issues/287 Reproducible example: is.object(freeny$y) # [1] TRUE attr(freeny$y, 'class') # [1] "ts" class(freeny$y) # [1] "ts" # ts attribute wiped by model.frame class(model.frame(y ~ ., data = freeny)$y) # [1] "numeric" attr(model.frame(y ~ ., data = freeny)$y, 'class') # NULL # but still:

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This one showed up while looking at one of Ripley's other reports: > data(freeny) > model.frame(y~1,data=freeny,subset=1:10) y 1962.25 8.79236 1962.5 8.79137 1962.75 8.81486 1963 8.81301 1963.25 8.90751 1963.5 8.93673 1963.75 8.96161 1964 8.96044 1964.25 9.00868 1964.5 9.03049 > model.frame(y~1,data=freeny,subset=1:10)$y Warning: Replacement length not a

This is not the same as the recent thread on a waterfall graph. I'm thinking about the rolling FFT display used in acoustics and other spectrum analysis tasks. Here's an example of a very fancy 3-D waterfall display: http://www.ultimaserial.com/UltimaWaterfall.html I was just wondering if there are any simple hidden-line tools in R that I could use to draw simple waterfall displays.

Let's say I have, for some reason, a bunch of scalars (i.e. single-valued variables) and I want to merge them all into a single vector of values. Can someone recommend a better function, or simpler way, to do so than the following? Suppose my scalars' names are foo1, foo2, foo3, foo1high, foo2high, foo3lo2, etc. Then I can do: >ls(pat='foo')->thels

Hi, While playing with quantile-quantile plots, I wrote up some code which plots something strangely different. Here's the pseudocode: testhist <- hist(sample_data) refhist <- hist(rnorm(n, mean=0,sd=1)) # for some large-ish n cumtest <- cumsum(testhist) cumref <- cumsum(refhist) plot(cumref,cumtest) This produces a straight line of slope 1 for a sample with the same

Hi, Sorry to bother with something that should be simple, but I can't find it. Suppose I have a list, each element of which is a 2xN dataframe, where N could be different for each element. Is there some simple structure to let me examine all the elements of each element's first column? For example: >foo $first [,1] [,2] [1,] 1 4 [2,] 2 5 [3,] 3 6 $second

Hi, So far as I can tell, the 'col.ticks' parameter for axis() only uses the first value provided. E.g.: plot(0:1,0:1, col.ticks=c('blue','red','green')) #all ticks are blue Just wondering if there's a different option in the basic plot commands that can handle multiple colors, and also whether ggplot and/or lattice allow for multiple tick colors.

Hi, I'm relatively new to R, so I don't know the full list of base (or popular add-on packages) functions and tools available. For example, I tripped across mention of rle() in a message about some other problem. rle() turned out to be a handy shortcut to splitting some of my data by magnitude (vaguely like a sequence-based histogram). So I thought I'd ask: what small, or

can you recommend a good manual for R that starts with a data set and gives demonstrations on what can be done using R? I downloadedR Langauage definition and An introduction to R but haven't found them overly useful. I'd really like to be able to follow some tutorials using a dataset or many datasets. The datasets I have available on R are Data sets in package 'datasets':

Hi, subject more or less says it all. I freely admit to not having bothered to find some of the online papers about method of testing the quality of random number generators -- but in an idle moment I wondered what to expect from something like the following: randa<-runif(1000) randb<-runif(1000) t.test(randa,randb)$p.value var.test(randa,randb)$p.value [repeat ad nauseum] Is the

I followed a couple threads from the archives and from stackoverflow.com, and would like to know: just what is "..." ? What I mean by this is,for example, from the point of view of a user running a function in debug mode, is "..." an object, or does it exist in the current environment as some thingy? Maybe a better question to ask is: if I were to write some function

Just wondering if there's an R package which does tricks similar to what TK!Solver does. TK!Solver, for those not lucky enough to have found it, basically allows one to define a bunch of equations, assign values to an arbitrary subset of the variables, from which it calculates (either directly when possible or back-solving when not) the values of the other variable(s). thanks Carl

Hi, I've got a matrix, Z, of values representing (as it happens) optical power at each pixel location. Since I know in advance I've got a single, convex peak, I would like to do a 2D parabolic fit of the form Z = poly((x+y),2) where x and y are the x,y coordinates of each pixel (or equivalently, the row, column numbers). Is there an R function that lets me easily implement that?