similar to: randomForest - partialPlot - Reg

Dear R Group I have a character vector from which I want to select a few elements and create a new character vector. I need a GUI to do this in R Script. Can someone help? a<-c("A","B","C","D","E") ## I want to have a GUI in R that will display elements in "object a" as a drop down list.. from there I want to be able to select a

Dear Group I have to populate a column in a R dataframe containing say 99 rows, where for every 3 row one row (randomly determined) of the column should take the value 1 and the other 2 row of that column should take the value 0. I used the command dataframe$new<-rep(sample(c(0,1,0),3,replace=FALSE),99) This command repeats the same patter of response across the entire column.. I would

Dear R Group Can any body point me to a link from where I can get zip archive of the package HH for R 2.12.0? Thanks & Regards Vijayan Padmanabhan "What is expressed without proof can be denied without proof" - Euclide. Please visit us at www.itcportal.com ****************************************************************************** This Communication is for the exclusive use

Hi R Forum I am a newbie to R and I have been amazed by what I can get my team to accomplish just by implementing Scripting routines of R in all my team's areas of interest.. Recently i have been trying to adopt R scripting routine for some analysis with longitudanal data.. I am presenting my R script below that I have tried to make to automate data analysis for longitudanal data by employing

@Don your solution does not solve Vijayan's scenario 2. I used spread and gather for that. An alternative solution to insert mising Fval - picking up with Don's newtst - is newtst <- c("FName: fname1", "Fval: Fval1.name1", "FName: fname2", "Fval: Fval2.name2", "FName: fname3", "FName: fname4", "Fval: fval4.fname4")

Using Ulrik?s example data (and assuming I understand what is wanted), here is what I would do: ex.dat <- c("FName: fname1", "Fval: Fval1.name1", "Fval: ", "FName: fname2", "Fval: Fval2.name2", "FName: fname3") tst <- data.frame(x = ex.dat, stringsAsFactors=FALSE) sp <- strsplit(tst$x, ':', fixed=TRUE) chk <-

Dear all, for each A == 3 in 'df' I would like to change the variables B and K. My result should be the whole df and not the subset (A==3)... df <- data.frame(A = c(1,1,3,2,2,3,3), B = c(2,1,1,2,7,8,7), K = c("a.1", "d.2", "f.3", "a.1", "k.4", "f.9",

Dear R Group I have a matrix object in R, where i want to retain only those columns which have each row from a different group.. see the example below.. team1<-c("a1","a2","b1","b2","b3","c1","c2") teams<-combn(team1, 3) I want a function which will delete all columns in the teams matrix that have more than 1 row

Dear R Group I have the following data for which I am trying to create subject wise lattice plot for a given attribute and product . though the lattice plot is generated, for some reasons that i dont understand in each plot the subject panels take a random order, I would rather want all the plots to display the subject order in the same order as how i have ordered this particular factor level.

Dear RGroup I have a requirement for which I am seeking help. I am looking at automating the last column calculation through R when having the data of the other columns as a dataframe, In excel I can do using the formula function as given below, however, hereagain for the number of observations that come under control, I need to write the formula seperately for each cell and then I can block

Hola erreros. A ver si alguien podría decirme qué son los dos ejes del plot que resulta de aplicar partialPlot en un Randomforest. Encuentro que: Partial dependence plot gives a graphical depiction of the marginal effect of a variable on the class probability (classification) or response (regression) que nos indica como varía la VR en función de la variable considerada, manteniendo el

I'm having trouble calling randomForest::partialPlot programmatically. It tries to use name of the (R) variable as the data column name. Example: library(randomForest) iris.rf <- randomForest(Species ~ ., data=iris, importance=TRUE, proximity=TRUE) partialPlot(iris.rf, iris, Sepal.Width) # works partialPlot(iris.rf, iris, "Sepal.Width") # works (function(var.name)

Dear RGroup I have a data of the type shown below: I am trying to use lme function followed by post hoc test as given in the code below. Am I right in my model definition, given the problem data structure. in the example, i have used column names of my data frame so that it is self explanatory. library(reshape) library(nlme) library(multcomp)

Hi Vijayan, one way going about it *could* be this: library(dplyr) library(tidyr) library(purrr) ex_dat <- c("FName: fname1", "Fval: Fval1.name1", "Fval: ", "FName: fname2", "Fval: Fval2.name2", "FName: fname3") data.frame(x = ex_dat) %>% separate(x, c("F1", "F2"), sep = ": ") %>% filter(F2

Muchas gracias Carlos; ¡tu siempre al pié del cañón! (lo puse el día de reyes a la 1.20h y me contestas a las 2.45h) Una cosa más: si el eje y es la probabilidad ¿por qué va de 0 a 10? En un RF para clasificación me da valores parecidos a los de tu ejemplo, y en otro para regresión, valores de y entre 45 y 55. Para regresión, el último parámetro no puede ser una categoría, como

Dear R-help Group Scenario 1: I have a text file running to 1000 of lines...that is like as follows: [922] "FieldName: Wk3PackSubMonth" [923] "FieldValue: Apr" [924] "FieldName: Wk3PackSubYear" [925] "FieldValue: 2017" [926] "FieldName: Wk3Code1" [927] "FieldValue: " [928] "FieldValue: K4" [929] "FieldName:

Dear R Users, I'm using the randomForest package and would like to generate partial dependence plots, one after another, for a variety of variables: m <- randomForest( s, ... ) varnames <- c( "var1", "var2", "var3", "var4" ) # var1..4 are all in data frame s for( v in varnames ) { partialPlot( x=m, pred.data=s, x.var=v ) } ...but this

Greg, Two thoughts: 1. It might be possible that 'vars' is a reserved word of sorts and if you change the name of your vector RF might be happier 2. A way that works for me is to call importance as follows: sel.imp <- importance(sel.rf, class=NULL, scale=TRUE, type=NULL) and then use the 'names' of the imp data frame to be absolutely clear to RF you are talking about the

Dear R Group in package Deducer, how should i use the add.cross.strata.test() function to pass the chi.squared.test function as htest argument? ##########Example########### library(Deducer) dat<-data.frame(a=rnorm(100)>.5,b=rnorm(100)>0,c=rnorm(100)>(-.5)) tables<-contingency.tables( row.vars=a, col.vars=b, stratum.var=c,data=dat)

Dear Group I was referring to a conjoint analysis scenario using R from the paper referred below: Agricultural Information Research 17(2),2008,86-94 available online at www.jstage.jst.go.jp/ This paper describes the data modelling of a conjoint study design based on conditional logit procedure. I understand that Heirarchical Bayes is asymptotically equivalent to Conditionallogit. However it