similar to: subset data.frame at C level

It looks to me like internally .subset2 uses `get1index()`, but this function is declared in Defn.h, which AFAIK is not part of the exported R API. Looking at the code for `get1index()` it looks like it just loops over the (translated) names, so I guess I just do that [0]. [0]: https://github.com/r-devel/r-svn/blob/1ff1d4197495a6ee1e1d88348a03ff841fd27608/src/main/subscript.c#L226-L235 On Wed,

Should the F statistic be the same when using add1() on models created by lm and glm(family=gaussian)? They are in the single-degree-of-freedom case but not in the multiple-degree-of-freedom case. MASS:addterm shows the same discrepancy. It looks like the deviance (==residual sum of squares) gets divided by the number of degrees of freedom for the term twice in add1.glm. Using anova() on the

I think you are not using the best function for what your intentions are. Try: > by(data=mtcars, INDICES=list(as.factor(mtcars$am)), FUN=colMeans) : 0 mpg cyl disp hp drat wt qsec vs 17.1473684 6.9473684 290.3789474 160.2631579 3.2863158 3.7688947 18.1831579 0.3684211 am gear carb 0.0000000

Dear all I'm unable to find an example of extracting the rotated scores of a principal components analysis. I can do this easily for the un-rotated version. data(mtcars) .PC <- princomp(~am+carb+cyl+disp+drat+gear+hp+mpg, cor=TRUE, data=mtcars) unclass(loadings(.PC)) # component loadings summary(.PC) # proportions of variance mtcars$PC1 <- .PC$scores[,1] # extract un-rotated scores of

Hola, Bueno, puedes hacer el cálculo de una forma mucho más compacta y rápida. Esta forma es especialmente recomendable cuando tienes muchas columnas y muchas filas. > library(data.table) > myDT <- as.data.table(mtcars) > myDTlong <- melt(myDT, measure.vars=1:ncol(myDT)) > myDTlong[ , list(p_value = shapiro.test(value)$p.value, v_stat = shapiro.test(value)$statistic) , by

I have created a DLL not so long ago using C code. My code used the IntegerFromString() function that used to be exported in the Rinternals.h header file (and thus easily accessible). Recently I upgraded to R 2.5.0 and my DLL stopped working. I see that the IntegerFromString() function is not exported in any of the header files in the RHOME\include directory. Is it possible for me to use it

Dear All, Thanks for your help. However, I would like to draw your attention to the following: Actually, I was replicating the Example 2.3, using the dataset "brainsize.txt" given in Section 2.3.3 ("Summarize by group") at page 55, of a famous book "R by Example" written by "Jim Albert and Maria Rizzo" published in Springers (2012) in a Use R! Series. The

Dear Sirs, I am Professor at Indira Gandhi Krishi Vishwavidyalaya, Raipur, Chhattisgarh, India. While taking classes, I found the *by() *function producing following error when I use FUN=mean or median and some other functions, however, FUN=summary works. Given below is the output of the example I used on a built-in dataset "mtcars", along with error message reproduced herewith: >

> On Apr 15, 2016, at 1:16 AM, Akhilesh Singh <akhileshsingh.igkv at gmail.com> wrote: > > Dear All, > > Thanks for your help. However, I would like to draw your attention to the > following: > > Actually, I was replicating the Example 2.3, using the dataset > "brainsize.txt" given in Section 2.3.3 ("Summarize by group") at page 55, > of a

Dear list, I want the 1st, 2nd, 5th, and 6th columns of mtcars. After copying them, the columns become numeric class rather than data frame. But, when I copy rows, they data frame retains its class. Why is this? I don't see why copying rows vs columns is so different. > class(mtcars) [1] "data.frame" > head(mtcars) mpg cyl disp hp drat wt qsec vs

Dear All, I have got your core message, that it is my responsibility to determine whether any particular function in my version of R satisfies the language requirements at the time of your use. Jim Albert and Maria Rizzo must have used their code, which was permitted in the R-code of their time (2012). Therefore, I have now modified my R-code, as per R-3..2.4 version, according to my requirement

I have applied the same linear model to several different subsets of a dataset. I recently read that in R, code should never be repeated. I feel my code as it currently stands has a lot of repetition, which could be condensed into fewer lines. I will use the mtcars dataset to replicate what I have done. My question is: how can I use fewer lines of code (for example using a for loop, a function or

> On Apr 16, 2016, at 2:03 AM, Akhilesh Singh <akhileshsingh.igkv at gmail.com> wrote: > > Dear All, > > I have got your core message, that it is my responsibility to determine whether any particular function in my version of R satisfies the language requirements at the time of your use. Jim Albert and Maria Rizzo must have used their code, which was permitted in the R-code

I have been successfully using RODBC for a long time (years) to connect to MS SQL Server from R. This week I wanted to try using odbc but I am seeing some problems which may be related to how I set up my driver and/or connection. The dbWriteTable manual page gives as an example command: dbWriteTable( pDB$con, "mtcars", mtcars[1:5,]) When I try this I get the following error Error:

Hi, I tried to do a multiple linear model from the example dataset Formaldehyde. However, the function lm() did not estimate the coefficient of the term carb^2. The same problem occurred with the (nlme)dataset Pixel with both function lme() and lm(). I am using the windows version of R 1.5.1 Lauri Mehtatalo The Formaldehyde example: > data(Formaldehyde) >

I would like to create a method for the generic function "with" applied to a class of fitted models. The method should do two things: 1. Substitute the name of the first argument for '.' throughout the expression 2. Evaluate the modified expression using the data argument to the fitted model as the first element of the search list. The second part is relatively easy. The

I want to use a strip.custom as with useOuterStrips for three conditioning variables. useOuterStrips restricts this to only two conditioning variables, and I cannot figure out how to write strip.custom properly to do this. library(lattice) mtcars$HP <- equal.count(mtcars$hp) #with two factors x2<-xyplot(mpg ~ disp | HP + factor(cyl), mtcars) useOuterStrips(x2) #with three factors

Hello R-help I don’t know how to interpret significance from the contr.poly() function . From the example below : how can I tell if data has a significant Linear/quadratic/cubic trend? > contr.poly(4, c(1,2,4,8))               .L         .Q          .C [1,] -0.51287764  0.5296271 -0.45436947 [2,] -0.32637668 -0.1059254  0.79514657 [3,]  0.04662524 -0.7679594 -0.39757328 [4,]  0.79262909 

Double quotes are not legal SQL syntax. Use single quotes. -- Sent from my phone. Please excuse my brevity. On August 29, 2017 2:21:44 AM PDT, Eric Berger <ericjberger at gmail.com> wrote: >I have been successfully using RODBC for a long time (years) to connect >to >MS SQL Server from R. >This week I wanted to try using odbc but I am seeing some problems >which >may be

Hi everyone, I've run into a bit of strange problem with implicit vs explicit printing and the call stack. I've included an example at the bottom of this email. The basic problem is that I have an S3 object with a print method. When the object is implicitly printed (ie. typed directly into the console) the function arguments in the call stack are exploded out to their actual values,