search for: meaningfully

Hi, today i wrote a function in R of the type: index.refraction <- function(Temp,Press, RH, CO2) When i try to plug a negative number in Temp, i got this type of error: " n <- index.refraction(Temp= -40,100,80,CO2) Messages d'avis : 1: In Ops.ordered(left, right) : '-' is not meaningful for ordered factors 2: In Ops.factor(left, right) : - not meaningful for factors 3:

Dear Experts, I need to include the repeated structure in our data set object, recall.sums.df, before using gls function. Thus I used groupedData. But I encountered error messages which may mean '*' is not not meaningful factor. Please let me know what I have to do. Thanks, Jeong > recall.sums.df[0:10, ] recall.values recall.ind subj replication hemi region group 1 17.515

Hi, I have a matrix with numbers and character. I want to evaluate each cell and change the value of the cell before it depending on the evaluation. My evaluation: if a cell had the word "down" change the cell preceding it to a negative number by multiplying that value by a -1. I am have trouble going back on clumn to make this change. I'm receiving an error on the j-1 part, and the

Hi, I have probably overlooked something obvious, but could anybody help me with following, please? Trying to make regression analysis. I have a huge dataframe with results from National Opinion Survey on Crime and Justice (www.abacon.com/fox/) with two variables G5 and N3 which are imported to R as ordered factors: > levels(noscj$G5) [1] "Strongly agree" "Agree"

Folks, I have a very basic question. The solution eludes me perhaps because of my own lack of creativity. I am not attaching a fully reproducible session because the issue may well be becuase of the way the data file is, and the data file is large (and I don't know whether I can legally distribute it). If people can suggest things that might be wrong in my data or the way that I am reading it,

Hello, Beginner, sorry if this is wasting anyone's time, but have been working on this for a couple of days now, think it should have take a few hours! The Problem: Error in Summary.factor(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, : max not meaningful for factors I have tried to re-arrange and check formula. I am working in SIAR, and cannot get model1 to run because of the error

Error in Math.factor(c(2L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 1L,  :   log not meaningful for factors In addition:Warning messages: 1: In Ops.factor(LRUpBound, LRLowBound) : * not meaningful for factors 2: In Ops.factor(TransitCoefStdDev, TransitCoefMean) :   / not meaningful for factors [[alternative HTML version deleted]]

Hi, can anyone help me in this problem :(. I am a total beginner in R software. It took me 2 days just to look into this problem. Due to this problem. I cant do looping. i want to find the distance between x and DSi > DSi i Si 1 1 (5, 20) 2 2 (20, 2) 3 3 (25, 32) 4 4 (8, 39) 5 5 (10, 17) 6 6 (35, 20) 7 7 (38, 10) > str (DSi) 'data.frame': 7 obs. of 2 variables: $ i

I am trying to define groupings from levels of factor variables and this the warning message that R give "& not meaningful for factors". The nature of my task is this. I have a variable stage which has the levels (1B, 2A, 2B) - these are the AJCC TNM stages of cancer, and another variable diameter with factor levels ("=< 4", "4 - 6.5, > 6.5; limit values are

Hi all, I can't come over a problem with formula. Suppose I have a coxmod model with the following formula: > somemod$formula Surv(lebzeit, tot == 1) ~ sex + (alter >= 65) + diff3k + zelltyp_k_c + q_nuc_3k + kar_k80_g80 + stadium and I want to drop the stadium explanatory variable from the model with > update(somemod, ". ~ . - stadium") I get the following messages:

Dear all, I try to summarise my data per category using aggregate, but for some reason I get the error message "sum" not meaningful for factors even though my vector is numeric. The data set is shown below. Could someone please give a hint. Thanks in advance! Sincerely, Tord > names(test) [1] "ObjektID" "tallstubbyta" > is.factor(test$ObjektID);

For some time now the tests in llvm-test/SingleSource/Regression and llvm-test/SingleSource/UnitTests have been producing no meaningful performance data other than "working". I think one of two things should be done, on a case-by-case basis: 1. Tests that are clearly simple, quick running tests should be moved into the llvm/test/Regression directory and made part of the deja-gnu suite

Hi everybody, Is there a particular reason, why this code does not work as intended: z <- factor(LETTERS[1:3], ordered = TRUE) u <- 4:6 min(z[u > 4]) Error in Summary.factor(2:3, na.rm = FALSE) : min not meaningful for factors I agree that min is indeed not meaningful for not ordered factors, but it makes sense for ordered factors. Especially since z[3] <

R 1.8.1: ___COMMAND____________________________________________ levelplot( yield ~ year * variety | site, barley ) ___ERROR_MESSAGE______________________________________ Error in Summary.factor(..., na.rm = na.rm) : "min" not meaningful for factors ___COMMENT____________________________________________ levelplot( yield ~ as.numeric(year) * as.numeric(variety) | site,

Windows 10 64-bit, R-Studio, R version 3.4.3 Several questions relating to groupedData: (1) I am trying to create a groupedData object that can be used to run an analysis that I have been able to urn using lmer. When I include the interaction terms in the groupedData opbject I get an error message stating that + is not meaningful for factors. How do I include factors in my model? See code and

Hello all, In yet another attempt to learn Ruby on Rails and Rspec I have started writing a simple life streaming app with will aggregate feeds from several places and save them in a database for later use. An internet search eventually led me to the following method for looping through the feeds in the database, getting the contents of the URL and then passing this into another model to prepare

Hi dear R-help memebers, When building a CART model (specifically classification tree) using rpart, it is sometimes obvious that there are variables (X's) that are meaningful for predicting some of the outcome (y) variables - while other predictors are relevant for other outcome variables (y's only). *How can it be estimated, which explanatory variable is "used" for which of

> Date: Fri, 7 Apr 2000 09:55:08 -0400 (EDT) > From: Faheem Mitha <faheem at email.unc.edu> [I have given a more meaningful subject line.] > On Fri, 7 Apr 2000, Prof Brian D Ripley wrote: > > > On Thu, 6 Apr 2000, Faheem Mitha wrote: > > > > > I'm running splus 5 on a solaris platform remotely, and running R on linux > > > on my home machine.

Hi, Currently object.size() is not very useful on environments as it always returns 56 bytes, no matter how big the environment is: env1 <- new.env() object.size(env1) # 56 bytes env2 <- new.env(hash=TRUE, size=75000000L) object.size(env2) # 56 bytes env3 <- list2env(list(a=runif(25000000), L=LETTERS)) object.size(env3) # 56 bytes This makes it pretty useless on

Herve, The problem then would be that for A a refClass whose fields take up N bytes (in the sense that you mean), if we do B <- A A and B would look like the BOTH take up N bytes, for a total of 2N, whereas AFAIK R would only be using ~ N + 2*56 bytes, right? ~G On Tue, Sep 29, 2015 at 2:42 PM, Herv? Pag?s <hpages at fredhutch.org> wrote: > Hi, > > Currently object.size()