similar to: Finding length of unique numbers in a vector

Hi all, I am trying to understand the R's "environment" concept however the underlying help files look quite technical to me. Can experts here provide me some more intuitive ideas behind this concept like, why it is there, what exactly it is doing in R's architecture etc.? I mainly need some non-technical intuitive explanation. Thanks,

Hi all, I am trying to understand the R's "environment" concept however the underlying help files look quite technical to me. Can experts here provide me some more intuitive ideas behind this concept like, why it is there, what exactly it is doing in R's architecture etc.? I mainly need some non-technical intuitive explanation. Thanks,

Dear all, I am a new user of R and currently trying hard to develop my own package. Here I am following this tutorial 'http://www.mathfinance.cn/how-to-create-an-R-package-in-windows/' Here it says that (step 8): "open a ?command prompt? window, change the directory to where your package is, type the command ?R CMD build MonteCarloPi? to build the package, this will generate a file

Hi there, given a numeric vector, I can select numbers within a specific range. However presently, I have something related but different problem. Suppose I have a numeric vector. Now take an arbitrary number. Goal to to chose a specific subset with a given length, from that given vector, so that those chosen numbers are centered around that given constant. Here is one example: ### My original

Hi all, I have created a package and now into writing it's help files. However I am having problem on, how to put a 'new line' in any statement of the help file? For example please consider following: \title{ This is a new function and this function will calculate the mean. } However I want to write it is this way: \title{ This is a new function & and, this function will

Hi again, yesterday I mailed this query however I could not see this on the mail list. Therefore, I am reposting it again. I was using package.skeleton() function to create the skeleton of my package in windows. Here is my attempt: rm(list = ls()) setwd("F:/R_PackageBuild") package.skeleton("trial1", namespace = TRUE, code_files = "F:/R_PackageBuild/trial.r") In

Hello I am struggling to accomplice an idea which is as follows: I have a vector say: a <- c("a", "b", "c", "a") and another: b <- c("m", "n", "o", "m"). Length of those 2 vectors are essentially be same. Here task is to check the duplicates in the vector 'a' and then to check whether any duplicates are

Hi all - I've been working on a lite ORM and database abstraction package for R. Formatting complex queries by hand has always been an error-prone hassle, so I've tried to do away with that as much as possible, instead, using R objects to represent elements of a database system (statements, clauses, operators, functions, fields, tables, etc.). R5 classes have made the development of this

Dear all, it is my first post in R-devel list, and hope that this is the right place to ask question related to package development. I have created my first package in Windows through the usual route. Now I want to add some ***Welcome message*** as soon as user loads my package into their R console, using library() function. However I could not figure out where and how should I add this

Hi all, I was trying to create some vignette files for my newly developed package, however wondering whether there could be any simpler way to do so. In writing R extension it is advised to go through Sweave route, however I have already got a big pdf file and want to use this as package vignette. So far I have manually created the inst/doc folder in the main package skeleton, and put that file

I would like to use samp as a part of a filename that I can change. My source files are .csv files with date as the file name, and I would like to be able to type in the date (later perhaps automate this using list.files) and then read the csv and write the pdf automatically. I have tried different combinations with "" and () around samp, but I keep getting the error "object

Hello guys, I would like to ask for help to understand what is going on in "func2". My plan is to generalize "func1", so that are expected same results in "func2" as in "func1". Executing "func1" returns... 0.25 with absolute error < 8.4e-05 But for "func2" I get... Error in dpois(1, 0.1, 23.3065168689948, 0.000429064542600244,

my reproducible example test<-structure(list(site = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L), .Label = c("A", "B", "C", "D", "E"), class = "factor"),

(To the list moderator: I just subscribed to the list. Apologies for not having done so longer before trying to post.) Hi all, I am currently using lmer to analyze data from an experiment with a single fixed factor (treatment, 6 levels) and a single random factor (block). I've been trying to follow the online guidance for estimating p-values for parameter estimates on these and other

I'm new to R (and to S) and am wondering about code from pages 72 and 83 of MASS (Venables+Ripley, 3rd edition), to draw an envelope on a QQ plot. Copying from the book, I've got: #... code whose gist is "a.fit <- nls(..." num.points <- length(resid(a.fit)) qqnorm(residuals(a.fit)) # illustrate data-model residuals qqline(residuals(a.fit)) samp <-

Hi, I am facing the problem that I want to plot a histogram chart set freq to true and overlay with normal or weibull or exponential distribution curve. The sample code is shown as below: >samp<-c(-8.2262,-8.2262,-8.2262,-8.20209,-8.09294,-8.07321,-8.07321, -8.07321,-8.07175,-8.04948,-8.04948,-8.04948,-8.03848,-8.03848,

Dear all, I am currently analyzing count data from a hierarchical design, and I?ve tried to follow the suggestions for a correct estimation of p-values as discusssed at R-Wiki (http://wiki.r-project.org/rwiki/doku.php?id=guides:lmer-tests&s=lme%20and%20aov). However, I have the problem that my model only consists of parameters with just 1 d.f. (intercepts, slopes), so that the

Dear R users I am trying to obtain p-values for (quasi)poisson lmer models, including Markov-chain Monte Carlo sampling and the command summary. > > My problems is that p values derived from both these methods are totally different. My question is (1) there a bug in my code and > (2) How can I proceed, left with these uncertainties in the estimations of > the p-values? > > Below

G'day all, looking at http://cran.at.r-project.org/web/checks/check_results_Sleuth2.html I noticed that r-prerel-* and r-devel-* issue notes. Apparently, now examples are more thoroughly checked by R CMD check and the note pointed out that a package used in the examples was not declared. This was easily fixed by adding 'Suggests: lattice' to the DESCRIPTION file (now this change has

Ccing the maintainer if the tuneR package. Looks to me like sawtooth (and square) don't behave as expected when using xunit="samples". Workaround is to use xunit="time" instead: sawtooth(110,duration=1/100,samp.rate=sample_rate,xunit="time") I looked at the code but found it to be opaque. -- Sent from my phone. Please excuse my brevity. On November 12, 2017