similar to: Extract rows with non-zero elements

Hello, I have two dataframes DF1 and DF2 that should be identical but are not (DF1 has some rows that aren't in DF2, and vice versa). I would like to produce a new dataframe DF3 containing rows in DF1 that aren't in DF2 (and similarly DF4 would contain rows in DF2 that aren't in DF1). I have a solution for this problem (see self contained example below) but it's awkward and

Dear all, Currently I am trying to integrate a function which depends on four variables, two of which are given, one is given in the integrate function, so there is one variable to integrate on. The code is as follows: Pmatrix = function(th) { P = matrix(nrow=6, ncol=6, data=0) P[1,1] = P[2,1]=P[3,2]=P[4,3]=P[5,4]=P[6,5]= exp(-th) P[,6] = 1-exp(-th) return(P)} lim.verd =

I have a large data frame 48:2185 with different numbers. I would like to add only one row at the very top of my data frame with 0's or NA's. I don't know which approach to use. Should i create 2 different data frames and merge them? Ive also tried the rbind command with no luck. I would appreciate some help to achieve what I'm trying to create. Thanks!

Hello list, I want to make a large rulebased algorithm, to provide decision support for drug prescriptions. I have defined the algorithm in a function, with a for loop and many if statements. The structure should be as follows: 1. Iterate over a list of drug names. For each drug: 2. Get some drug related data (external dataset). Row of a dataframe. 3. Check if adaptions should be made to

I'm running a Windows program with Wine under Linux (Red Hat), but I'm having problems with the thousand and decimal separators. The Linux OS is set to en_US. When I tab through an inputfield with a decimal value e.g. 1,00 it'll change to 100,00. This is really tricky, because values are changed to complete different values. I've been trying to change the regional settings by

Hi everyone, Im quite new to R an I have the following Question: I would like to define Variables which I can add and multiply etc. and that R can simplyfy the terms. The variables should stand for integers. For example I would like to have an entry in an array with variable z and if I add b+z the field should now contain 2z+b. Or if the field contains 1 and I add z

Hello R users, My problem is that the data I've got is in the minimum number of columns with each ward (geographic area) appearing multiple times. The first 30 terms look like this > HHum02 CASW Btype Yr CO2Group NumVeh 170597 00CCFA CARS 2002 C 2 170598 00CCFA CARS 2002 D 2 170599 00CCFA CARS 2002 E 22 170600 00CCFA CARS 2002

Estimados miembros de la lista, Estoy trabajando con la función spin del paquete knitr y no puedo entender por que a pesar de usar #+ para iniciar cada chunk no reconoce el inicio de un nuevo chunk al menos que incluya texto entre cada inicio de chunk. En el ejemplo abajo #+ data(cars) #+ cars No los separa como 2 chunks diferentes Ejemplo de mi archivo en r (prueba.R)

Muchas gracias Carlos. Tengo la versión de knitr 1.14 Corrí el ejemplo que me dices y resulta en lo mismo, no se crean chunks diferentes. Parece que para separar chunks se debe incluir #' Por ejemplo, estas 2 líneas de códigos del ejemplo: #+ test-chisq5 sum(x^2) # chi-square distribution with df 5 #+ test-chisq4 sum((x - mean(x))^2) # df is 4 now Dan como resultado en el Rmd (todo queda

I am just getting the hang of this, so forgive me if this is a stupid question... - I have two models/tables: Owners and Cars - Owners may have many cars. Cars have one owner. - Cars have a property named Color. Question: how do I get a list of all the Owners who have RED cars? I want something like this to work: Owner.find_by_car.color("RED") Thanks for any help! -- Posted via

Hi R help, Hi R help, Which is the easiest (most elegant) way to force "aov" to treat numerical variables as categorical ? Sincerely, Andrea Bernasconi DG PROBLEM EXAMPLE I consider the latin squares example described at page 157 of the book: Statistics for Experimenters: Design, Innovation, and Discovery by George E. P. Box, J. Stuart Hunter, William G. Hunter. This example use

Dear All, I've been?searching for?appropriate codes to compute the rate of change and the curvature?of ?nonparametric regression model whish was denoted by a smooth function?but?unfortunately?don't manage to?do?it. I presume that such characteristics from a smooth curve can be determined by the first and second derivative operators. The following are the example of fitting a

Please allow me an unusual question. Is there any way that R can be closely integrated with a Microsoft Powerpoint presentation? I would like to embed R calculations in Powerpoint so that I will start Powerpoint, be prompted to enter some parameters, and an R function will run and return values and graphs. Thanks, John R 2.1.1 windows 2k John Sorkin M.D., Ph.D. Chief, Biostatistics and

Muchas gracias Carlos. Tengo las mismas versiones pero no logro separar los chunks cuando uso #+, pero si lo logro cuando uso #". Mi script es spin("prueba.R", knit = FALSE) y si me hace un Rmd. #+ a = c(1,2,3) #+ mean(a) Ejecuto, > spin("prueba.R", knit = FALSE) y obtengo un prueba.Rmd ```{r } a = c(1,2,3) ```{r } mean(a) ``` Pero si escribo: #' a =

I like the functionality provided by outer=TRUE, but when it comes time to place separate xlabs or ylabs, I always end up 'eyeballing' it on a case-by-case basis. For example, ##begin example require(lattice) cars.lo <- loess(dist ~ speed, cars) print(xyplot(cars.lo$residuals+cars.lo$fitted~cars.lo$x, strip=FALSE, outer=TRUE, layout=c(1,2),

Dear all, To draw a lowess line on a plot was a piece of cake; to draw a loess line, however, seems not that easy. Is the loess plotting implemented at all in relation to the loess function, or do I have to look in add-on packages? Thanks, Marcin

hola soy nuevo usuario de R y necesito crear un objeto p tal que, p=lambda*integral[f´´(x)^2 dx ] donde "lambda" es uno de los parametros que resultan de la funcion "smooth.spline()" y la integral es sobre la derivada 2 de esa misma funcion... dos cuestiones: 1) como extraigo lambda de los resultados de smooth.spline() para usarlo como objeto cuando lo requiera y 2) como

Hello all and thank you for reading this message. I am new to RoR, and ruby too, but i am quite excited about it. I am developing a RoR project and with active record associations in the following manner # Tables (all tables have only one record) CREATE TABLE `webcars_development`.`cars` ( `id` int(11) NOT NULL auto_increment, `model_id` int(11) NOT NULL default ''0'',

I am working on a reproducible computing platform for which I would like to be able to _exactly_ reproduce an R object. However, I am experiencing unexpected randomness in some calculations. I have a hard time finding out exactly how it occurs. The code below illustrates the issue. mylm1 <- lm(dist~speed, data=cars); mylm2 <- lm(dist~speed, data=cars); identical(mylm1, mylm2); #TRUE

Hi all, I'm trying to apply loess regression to my data and then use the fitted model to get the *standardized/studentized residuals. I understood that for linear regression (lm) there are functions to do that:* * * fit1 = lm(y~x) stdres.fit1 = rstandard(fit1) studres.fit1 = rstudent(fit1) I was wondering if there is an equally simple way to get the standardized/studentized residuals for a