similar to: conditional IF with AND

Hi all, I have a large dataset that has >10k entries. The dataset is stored in a dataframe with the headers: SubID Condition1 Condition2 Result1 Result2 There are multiple entries for a given SubID(Subject ID). Condition 1 has 3 levels and condition2 has 2 levels (therefore there are 6 possible combinations all together e.g. Cond1 Level1 x Cond2 Level 1 etc.) and i need to compute for 1. The

Hi All: Let's say I have two dataframes (Condition1 and Condition2); each being on the order of 12,000 and 16,000 rows; 1 column. The entries contain dates. I'd like to calculate, for each possible pair of dates (that is: Condition1[1:10,000] and Condition2[1:10,000], the number of days difference between the dates in the pair. The result should be a matrix 12,000 by 16,000. Really,

Hi everyone, I want to perform an operation on a matrx that outputs the product of successive pairs of rows. For example: calculating the product between rows 1 & 2; 3 & 4; 5 & 6...etc. Does anyone know of any readily available functions that can do this? Thanks, rcoder -- View this message in context: http://www.nabble.com/product-of-successive-rows-tp18681259p18681259.html

I spent some time on this simple question, also searched the forum, eventually hacked my way to an ugly solution for my particular problem but I would like to improve my coding: I have data of the form: df <- expand.grid(group=c('copper', 'zinc', 'aluminum', 'nickel'), condition1=c(1:4)) I would like to add a new data column "condition2", with values

Dear R Experts, I am attempting to run a mixed effects model on a within-subjects repeated measures design, but I am unsure if I am doing it properly. I was hoping that someone would be able to offer some guidance. There are 5 independent variables (subject, condition, difficulty, repetition) and 1 dependent measure (value). Condition and difficulty are fixed effects and have 3 levels each

Dear all, I'm routinely using lattice and ggplot2, I wish to create a lattice theme that looks not too dissimilar to ggplot's defaults so I can include both graphs in a document with a consistent look. To illustrate my questions, consider the following example: > library(ggplot2) > library(lattice) > > # example data > x <- seq(0, 10, len = 100) > y1 <-

Hello everyone, I bring to discussion the necessity/design of a new type of smart pointer. r215176 and r217791 rise the problem, D5443 <http://reviews.llvm.org/D5443> is devoted to the solution. r215176 applies several temporary ugly fixes of memory leaks in TGParser.cpp which would be great to be refactored using smart pointers. D5443 <http://reviews.llvm.org/D5443> demonstrates

Dear list members, I want to perform in R the analysis "simultaneous confidence interval for multiple proportions", as illustrated in the article of Agresti et al. (2008) "Simultaneous confidence intervals for comparing binomial parameter", Biometrics 64, 1270-1275. If I am not wrong the R function implementing the Agresti et al. method is prop.test(). I ask an help because I

Hi, I am performing experiments in the field of visual perception where we often apply balanced designs. Within a group of normal subjects, we vary different stimulus conditions (like contrast, luminance, temporal frequency of stimulation) and derive some psychophysical or electrophysiological results from our subjects. Often, the main question is to test the effect of these parameters

Hi everyone, I have a matrix that has a combination of zeros and NAs. When I perform certain calculations on the matrix, the zeros generate "Inf" values. Is there a way to either convert the zeros in the matrix to NAs, or only perform the calculations if not zero (i.e. like using something similar to an !all(is.na() construct)? Thanks, rcoder -- View this message in context:

Dear R-Users, I would like to know whether it is possible to draw several stacked barplots (i.e. side by side on the same sheet)... my data look like : Cond1 Cond1' Cond2 Cond2' Compartment 1 11,81 2,05 12,49 0,70 Compartment 2 10,51 1,98 13,56 0,85 Compartment 3 1,95 0,63 2,81 0,22 Compartment 4 2,08 0,17

Dear list, I have data like this: dat1 <- data.frame(subject=rep(1:10,2), cond1=rep(c("A","B"),each=5), cond2=rep(c("C","D"),each=10), choice=sample(0:1,10,replace=TRUE)) I would like to compare subjects' "choice" for (cond1=="A" & cond2=="C") vs

Hi everyone, I posted something similar to this in reply to another post, but there seems to be a problem getting it onto the board, so I'm starting a new post. I am trying to use conditional formatting to select non-zero and non-NaN values from a matrix and pass them into another matrix. The problem is that I keep encountering an error message indicating the ":missing value where

Hi everyone, I'm having some trouble with my ifelse statements. I'm trying to put 12 conditions within 3 groups. Here is the code I have so far: dat$cond <- ifelse(test = dat$cond == "cond1" | dat$cond == "cond2" | dat$cond == "cond3" dat$cond == "cond4" yes = "Uniform" no = ifelse(test =

Some InstCombine transforms for select-of-select were added here: https://reviews.llvm.org/rL228409 But Alive says this is more poisonous: Name: selsel %s1 = select i1 %cond1, i8 C1, i8 C2 %s2 = select i1 %cond2, i8 %s1, i8 C2 => %andcond = and i1 %cond1, %cond2 %s2 = select i1 %andcond, i8 C1, i8 C2 http://rise4fun.com/Alive/JT6 Are those transforms legal? -------------- next part

Hi, I have a general question on LoopUnswtich pass. Consider the following IR snippet: define i32 @test(i1 %cond) { br label %loop_begin loop_begin: br i1 %cond, label %loop_body, label %loop_exit loop_body: br label %do_something do_something: call void @some_func() noreturn nounwind br label %loop_begin loop_exit: ret i32 0 } declare void @some_func() noreturn After running

I am evaluating a switch from Stata to R. I don't need to extensive Statistical methods, but the main reason I am exploring the switch is the coding flexibility in R (e.g. Stata does not support linear/quadratic programming). I have been going over the R syntax and I had a quick question: In Stata, one has a very useful construction called "by", e.g. by month signal: gen xxx =

I know how to convert a simple dataframe from wide to long format with one varying factor. However, for a dataset with two factors like the following, Subj T1_Cond1 T1_Cond2 T2_Cond1 T2_Cond2 1 0.125869 4.108232 1.099392 5.556614 2 1.427940 2.170026 0.120748 1.176353 How to elegantly convert to a long form as Subj Time Cond Value 1 1 1 0.125869 1

Hello everyone, I am working for a few days already on a basic algorithm, very common in applied agronomy, that aims to determine the degree-days necessary for a given individual to reach a given growth stade. The algorithm (and context) is explained here: http://www.oardc.ohio-state.edu/gdd/glossary.htm , and so I implemented my function in R as follows: DD <- function(Tmin, Tmax, Tseuil,

Hi all, suppose there is a vector y with rownames: > y cond1 cond2 cond3 cond4 78.952 87.308 86.490 74.040 how can I easily plot this vector using the rownames? plot(y) gives me a plot with a x-axis from 1 to 4 in 0.5 steps, also plot(rownames(y), y) and plot(y ~ rownames(y) don't work. I know I can build a x-axis with axis(1, ...), but in this case I need a character string like