similar to: help with simple function

I am trying to set up a function which processes my data according to the following rules: 1. if (x[i]==0) NA 2. if (x[i]>0) log(x[i]/(number of consecutive zeros immediately preceding it +1)) The data this will apply to include a variety of whole numbers not limited to 1 & 0, a number of which may appear consecutively and not separated by zeros. Below is an example with a detailed

This is a very simple question but I couldn't form a site search quesry that would return a reasonable result set. Say I have a vector: x <- c(0,2,3,4,5,-1,-2) I want to replace all of the values in 'x' with the log of x. Naturally this runs into problems since some of the values are negative or zero. So how can I replace all of the positive elements of x with the log(x) and the

I am trying to fit a very simple broken stick model using the package "segmented" but I have hit a roadblock. > str(data) 'data.frame': 18 obs. of 2 variables: $ Bin : num 0.25 0.75 1.25 1.75 2.25 2.75 3.25 3.75 4.25 4.75 ... $ LnFREQ: num 5.06 4.23 3.50 3.47 2.83 ... I fit the lm easily: > fit.lm<-lm(LnFREQ~Bin, data=id07) But I keep getting an error

Hi all, Suppose I want to set the values in a column to the log of the values of another column like so: object$LogDist <- log10(object$Distance) How do I loop through the objects if I have object1, object2, etc to perform this function? object1$LogDist <- log10(object1$Distance) object2$LogDist <- log10(object2$Distance) object3$LogDist <- log10(object3$Distance) I was trying to

I would expect that several math operations should always return values with a class of numeric. If the input is defined with multiple classes, however, the class attribute is preserved. I would think this may have some unintended side-effects. Here's an example: > sessionInfo()$R.version$version.string [1] "R version 3.4.0 (2017-04-21)" > x <- seq.int(5) >

I think you may be confusing (S3) class and ?mode. > x <- seq.int(1:3) > class(x) [1] "integer" > mode(x) [1] "numeric" > class(x+.5) ## coercion [1] "numeric" > mode(x+.5) [1] "numeric" But note: > y <- as.integer(1) > class(y) [1] "integer" > class(y) <- "foo" > mode(y) [1] "numeric" >

Thanks Bert, I think we agree on the current behaviour, but I'm still not sure if it's desirable. The mode isn't used for method dispatch. In the following example, I have to write `log.foo` in order for the correct method to be called. > x <- seq.int(5) > class(x) <- c("integer", "foo") > half <- function(x) UseMethod("half") >

Am I trying to perform multiple linear regressions on each 'VARIABLE2'. I figured out that there are different ways, using the following code: (data is given at the end of this message) reg <- lapply(split(TRY, VARIABLE2), function(X){lm(X2 ~ X3, data=X)}) lapply(reg, summary) Which produces the following: $`1` Call: lm(formula = X2 ~ X3, data = X) Residuals: Min

Hi, I start with an array of booleans: x <- c( TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE, TRUE ); I want to define an y <- f(x) such that: y <- c( 1, 2, 3, 0, 0, 1, 2, 0, 1 ); In other words, do a cumsum when I see a TRUE, but reset to 0 if I see a FALSE. I know I can do this with a very slow and ugly loop or maybe use apply, but I was hoping there are some R experts out

Hello, first of all, thanks to LT for \pkg{codeutils}. I agree that it is indeed very useful to identify errors and also to encourage re-thinking past solutions. My problem: I want to compare different sets of related sub-functions which should be used alternatively by the same top-level function. Sets of related functions should be bound together (as lists) and the workspace should be as clean

Hi, I'm experimenting with a few learners that require a matrix as their input. (Currently svmpath, vbmp, etc.) I currently have a dataframe with 50 columns and 20,000 rows. I tried using: x <- as.matrix(my_data.frame) If I then as, "is.matrix(x)", I get TRUE. However everywhere I've tried to use the matrix returns errors. Is there a step I'm missing? Thanks! -N

Hi Elisa, I hope this is what you wanted. dat1<-read.csv("peaks.csv",sep=",") #Subset dat2<-dat1[1:5,] res1<-do.call(cbind,lapply(seq_len(nrow(dat2)),function(i) do.call(rbind,lapply(split(rbind(dat2[i,],dat2[-i,]),1:nrow(rbind(dat2[i,],dat2[-i,]))), function(x) {x1<-rbind(dat2[i,],x);

Fellow R-helpers, Suppose we create a histogram as follows (although it could be any vector with zeroes in it): R> lenh <- hist(iris$Sepal.Length, br=seq(4, 8, 0.05)) R> lenh$counts [1] 0 0 0 0 0 1 0 3 0 1 0 4 0 2 0 5 0 6 0 10 0 9 0 4 0 [26] 1 0 6 0 7 0 6 0 8 0 7 0 3 0 6 0 6 0 4 0 9 0 7 0 5 [51] 0 2 0 8 0 3 0 4 0 1 0 1 0 3

I have two data matrices that I want to make the correlation between each column from data1 and each column from data 2 and also calculate the p-value Matrices dont have the same size and I tried such a script. > bg <- read.table (file.choose(), header=T, row.names) > bg > Otu00022 Otu00029 Otu00039 Otu00042 Otu00101 Otu00105 Otu00125 Otu00131 Otu00137 Otu00155 Otu00158 Otu00172

Hi, I have two data frames (u and v). > u   coe      nam 1   0     Time 2   0    Poten 3   0   AdvExp 4   0    Share 5   0   Change 6   0 Accounts 7   0     Work 8   0   Rating > v       coeff    enter 1 0.7272727 Accounts 2 0.3211112     Time 3 0.0500123    Poten I want to update the values of coe in u by using the values ofcoeff in v. That is, I want to get the following result >

This issue has arisen within my anova.coxph routine, but is as easily illustrated with glm. testdata <- data.frame(y= 1:5, n= c(8,10,6,20,14), sex = c(0,1,0,1,1), age = c(30,20,35,25,40)) fit <- glm(cbind(y,n) ~ age + sex, binomial, data=testdata, model=TRUE) saveit <- fit$model update(fit, .~. - age, data=saveit)

Is there any way to identify or infer the inflection points in a smooth spline object? I am doing a comparison of various methods of time-series analysis (polynomial regression, spline smoothing, recursive partitioning) and I am specifically interested in obtaining the julian dates associated with the inflection points inferred by the various models. Tyler e.g.

hi all, Assume I have data like data<-rbind(c(1,2),c(1,3),c(2,1),c(3,2),c(3,4)) I want to get some matrix like 1,2,3 2,NA,NA 3,2,4 I'm using by mat<-matrix(NA,3,3) by(data,data[,1],mat[data[,1],]<-c(data[,2])) but it doesn't work. Any ideas? thanks, cowboy

Define an array > v<-1:256 > dim(v)<-rep(4,4) Subarrays can be obtained as follows: > v[3,2,,2] [1] 71 87 103 119 > v[3,,,2] [,1] [,2] [,3] [,4] [1,] 67 83 99 115 [2,] 71 87 103 119 [3,] 75 91 107 123 [4,] 79 95 111 127 In the general case this procedure is very tedious. Given an array A, dim(A)=(dim_1,dim_2,...,dim_d) and two vectors

R friends, I am using R 2.1.0 in a Win XP . I have a problem working with lists, probably I do not understand how to use them. Lets suppose that a set of patients visit a clinic once a year for 4 years on each visit a test, say 'eib' is performed with results 0 or 1 The patients do not all visit the clinic the 4 times but they missed a lot of visits. The test is considered positive if it