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Sorry about the subject --- On Thu, 24/9/09, KABELI MEFANE <kabelimefane@yahoo.co.uk> wrote: From: KABELI MEFANE <kabelimefane@yahoo.co.uk> Subject: Re: [R] Multiply Normal Curves To: R-help@r-project.org Date: Thursday, 24 September, 2009, 11:48 AM R -helpers   i have been trying to do this problem without must success,i managed to do a graph for x, but it is not what i want to

 Dear All   let me go one step further by asking you if you could help me show that the distribution of this data in normal.  have a little idea (by trial and error) but i seem to not fully understand how its done.   H<-rnorm(100, mean=50000, sd=3000) par(las=1) hist(H, breaks=seq(40000, 60000, 1000), freq=F) f<- function(x) exp(-(x-5000)^2/18000000)/sqrt(18000000*pi)  x<- seq(40000,

Dear Helpers   I have a sample frame and i have sampled from it using three methods and now i want to calculate the statistics but i only get the population parameters.   H <- matrix(rnorm(100, mean=50000, sd=5000)) sampleframe=data.frame(type=c(rep("H",100)),value=c(H)) sampleframe   str=strata(sampleframe,c("type"),size=c(20,), method="srswor")

R -helpers   i have been trying to do this problem without must success,i managed to do a graph for x, but it is not what i want to define. I have also been able to do simple rendom sample. If possible can someone help here is the code for the graph pleae help   data.frame(ID=c(1,2,3),mu=c(10000,34000,50000),sigma=c(2000,3000,5000)) curve(dnorm(x,mean=parms$mu[1],sd=parms$sigma[1]),from=2000,

R-list   I am sorry for asking this stupid question, but i have been running in circles. I want to randomly generate a scaling point of between 1 and 10, for say hundred entries, where the first 10% percent is has rates between 2 and 7, the next 15% 3 and 7, 20% between 3 and 9, 20% between 3 and  10, 35% between 5 and 10. The problem is that i can only generate the usual 100 using runif function

R helpers   Please help me combine the simulated data to a form of table where: Hypermarket have 10 rows, supermarket have 15 rows,......., spazashops with 35 rows.   Hypermarket <- rnorm(10, mean=20000, sd=7000) Supermarket <- rnorm(15, mean=12000, sd=4000) Minimarket   <- rnorm(20, mean=10000, sd=4000) Cornershop  <- rnorm(20, mean= 8000, sd=3000) Spazashop   <- rnorm(35, mean=

Dear All ? I know that you do not have to help me but please do, i am new to R as a CPI compiler, i just need to do a sample to see which sampling method best works in different situations, therefore since this is for practice purposes nobody will finance a real project thats why i need you to help me direct me as to how simulate data (just direct me,not 100% help). See my attachment for problem

Hello! Up to now I have been using hist() to display the distributions. Howevere, I noteiced strange numbers on y (vertical) axis, if I used probability = T or freq = F option. I thought it is a bug and launched the R-bug system and found some posts on that matter. Brian Ripley responded to one, that one should look at truehist() for that. Ok I can use truehist() if I want to see the ratios

Hi there, # Consider the following example: A = 19 B = 20 A< B A==B hist(c(1:15,B,50),breaks=c(0,15,A,50),plot=F)$count hist(c(1:15,A,50),breaks=c(0,15,B,50),plot=F)$count # I was expecting the same results with the following values of A and B: A = 19.6019203953960 B = 19.6019204365543 A< B A==B hist(c(1:15,B,50),breaks=c(0,15,A,50),plot=F)$count# wrong

I can't seem to get a histogram of dates: tmt910% R --vanilla R version 2.13.0 (2011-04-13) Copyright (C) 2011 The R Foundation for Statistical Computing ISBN 3-900051-07-0 ... > temp <- as.Date(1:200, origin="1970/01/01") > range(temp) [1] "1970-01-02" "1970-07-20" > hist(temp) Error in .Internal(inherits(x, what, which)) : 'x' is missing

rdevel from yesterday, also in 1.9.1 (Debian, -3). The man page of 'hist' (from the graphics package, obtained by "?hist") suggests 'truehist' under "see also", but 'truehist' isn't loaded by default (a sensible "of course"), so that "?truehist" fails. One can do help.search(), of course, which points what to do, but leads to my

Hi, Is this a bug in truehist()? > library(MASS) > x <- rep(1, 10) > truehist(x) Error in pretty(data, nbins) : invalid 'n' value Thanks, Gad > R.version platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status major 2 minor 4.1 year 2006 month 12 day 18 svn

Hi, Is this a bug in truehist()? > library(MASS) > x <- rep(1, 10) > truehist(x) Error in pretty(data, nbins) : invalid 'n' value Thanks, Gad > R.version platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status major 2 minor 4.1 year 2006 month 12 day 18 svn

>selectiris<-sample(1:5, 150, replace=T) > hist(selectiris, plot=TRUE) #freq=TRUE, breaks=5, etc all do the same thing >truehist(selectiris) Is the behavior of "hist" in this sample of code correct. On my system (Windows 2K, SP2) the first and second bars are pushed together, while the 3rd, 4th, and 5th bars are correctly positioned. The function "truehist"

hi all : i have the data below and then below that, i call the hist function three times using the Scott method for the widths of the bins. the bin width is different for the three histograms but I would like it to always be 0.05 regfardless of the data set being histogrammed. I'm sure there must be a manual way to do this which is fine with me. i tried breaks=0.05 but it wasn't happy

Hi, This is a very basic question, but I would like to undestand hist(). I thought that the hist( , freq=FALSE) should provide the relative frequencies (probabilities), and so they should sum 1, however: set.seed(2) ah <- hist(rnorm(100), freq=F) sum(ah$intensities) [1] 2 set.seed(2) bh <- hist(rlnorm(100), freq=F) sum(bh$intensities) [1] 0.4999996 I'm getting similar figures with

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, According to the Sturges rule, the number of classes of a histogram is the closest integer to 1 + logb(n,base=2) where n is the number of observations. The function hist(), by default, uses the Sturges rule. However, the code x <- 1:200 hist(x) produces a histogram with 10 classes and not 9 classes as determined by the Sturges rule. What am I missing? Thanks in advance, Paul

Dear People, I have a data set of data x from a probability distribution, and I have a function, mydensity, of the pdf of that distribution. I'm asking for help in superimposing the histogram of x and the plot of mydensity. In the function below, I call truehist and curve, but these are plotted in different figures. I'd like them to be plotted on the same figure, and to use common

I am trying to plot a lognormal density curve on top of an existing histogram. Can anybody suggest a simple way to do this? Even if someone could just explain how to plot a regular normal density curve on top of an existing histogram, it would be a big help. Also, is there some way to search through the R-help archives other than simple browsing? Thank you so much. Your help and time is greatly