similar to: How to change the number of bins in "hist" function?

Hello R-list, I've been using hist to plot histograms of some data, but I get variable numbers of bins. I understood from reading the help file that breaks will set the number of bins. Please correct me if I'm wrong. I'm plotting measures from subsets of a larger data set. Depending on the data subset the number of bins varies despite having set breaks to 5 in all cases. See

Think I'm missing something to understand what is going on with hist(...) http://n2.nabble.com/What-is-going-on-with-Histogram-Plots-td3022645.html For my example I count 7 unique years, however, on the histogram there only 6. It looks like the bin to the left of the tic mark on the x-axis represents the number of entries for that year, i.e. Frequency. I guess it looks like the bin for

Dear all, I have a binned data that looks like this: > dat (-1,9] (9,19] (19,29] (29,39] (39,49] (49,59] (59,69] (69,79] 10063374 79 16 4 3 4 4 3 (79,89] (89,99] 6 2 I tried to plot a histogram overlayed with curve. With the following snippet: library(lattice) pdf("myfile.pdf") hist(dat)

Is it possible to change the x-axis values in a histogram to reflect binned values? Here are my data: histexample<-c(6,7,7,8,8,8,9,9,9,9,9,10,10,10,10,10,10,10,11,11,11,11,11,11,12,12,12,12,13,13,13,14,14,14,15,16) hist(histexample) Now, I'll bin pairs of adjacent values together (e.g., 5-6, 7-8, 9-10, 11-12, 13-14, 15-16) using the following bins<-c(4.5,6.5,8.5,10.5,12.5,14.5,16.5)

Hi, I have a set of observations which are divided into two sets A and B. I have some code that bins the dataset into 10 bins based on the max and min of the observed values. I would like to make a histogram of A & B using my calculated bins but plot the distribution of B on top of A (like a stacked barplot). This is possible since both sets A & B are binned using the same bin ranges.

Hi R-users, I am trying to divide a vector (say X) into equal frequency bins. If one uses the hist() function, then a histogram is plotted, but with bins of equal widths, and not with bins having the same number of data points. I have then tried the histogram() function as follows: histogram(X, nint=10, breaks=NULL, equal.widths=F) This works as I want. However, I can't extract which

When preparing a series of histograms I found that hist was combining the two lowest categories or bins, 1 and 2. Specifying breaks, as illustrated below, resulted in the correct histogram: values <- sample(10,500,replace=TRUE) hist(values) hist(values,breaks = 0:10) Apparently, the number of values strictly less than 1 is shown in the first bin (and since none is less than 1,

Hi Folks, I'd like to know how hist() decides how many cells to use when it ignores my "suggestion" to use say 'hist(...,breaks=50)'. More specifically, I have the results of 10000 simulations, each returning an 8-vector, therefore 8 variables each with 10000 values. Some of these 8 have somewhat skew distributions. Say one of these 8 variables is X. I ask for H <-

Hello all. I noticed that the default setting for breaks in the construction of histograms in hist() is ?right = TRUE?. I think ?right=FALSE? would be more consistent with usual definitions of lower and upper limits for bins in applied statistics, and I suggest that you consider making it the default for hist(). For example, I generated the following frequency distribution for duration of

I think there are a couple of things in ?hist that are not quite as clear as they could be. (1) freq: logical; if 'TRUE', the histogram graphic is a representation of frequencies, the 'counts' component of the result; if 'FALSE', _relative_ frequencies ("probabilities"), component 'density', are plotted. Defaults to

Hi, I have a couple of observations, a question or two, and perhaps a suggestion related to the plotting of density on the y-axis within the hist() function when freq=FALSE. I was using the function and trying to develop an intuitive understanding of what the density is telling me. After reading through this fairly helpful post:

The command hist(c(2,2,2,4,5,6)) returns a histogram that looks incorrect -- 3 in the bin labeled 2 on the left, but 1 each in the bins labeled 3,4,5 on the left. Thanks! Pam Surko -------------------- > version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 1 minor

Dear listers, A quick question about breaks in hist(). The histogram is highly screwed to the right, say, the range of the vector is [0, 2], but 95% of the value is squeezed in the interval (0.01, 0.2). My question is : how to set the breaks then make the histogram look even? Thanks in advance, Leaf

Hi, I have a casting/formatting question on hist.POSIXt: The histogram plot from POSIXct works perfect (with help of Prof. Ripley -thanks!). When processing the hist(plot=FALSE) output and then plotting the results over the x-axis (bins) coming from hist(), I lose the date/time labels, getting instead integers displayed. Trying to cast the $breaks with as.POSIXct gives silly results with

Hi R users, My goal is to rank my samples according to how they fall out in a histogram with 10 bins to produce a ranking for each sample according to where it falls on the histogram, with a "1" to represent one tail of the hist, a "10" to represent the other tail, and a "5" for the median/mean. I have a number of different data sets to do this with and in all cases

Hi all, I need some help using read.ftable to read a contingency table. My columns are organized as follows: order--family--species--location--number of individuals I couldn't figure out how to change the data on my text file to be imported into R; and after you do that, is it possible to convert the table into a data frame? Any tips would be greatly appreciatted! Thanks a lot, Naiara.

Hi, I am using coxph in simulations and I want to store the "robust se" (or "se2" in frailty models) for each replicate. Is there a function to retrieve it, like vcov() for the variance estimate? Thanks! Lei Liu Assistant Professor Division of Biostatistics and Epidemiology Dept. of Public Health Sciences School of Medicine University of Virginia 3181 Hospital West

I use mnp to run a multinominal probit regression model, but the summary doesn't contain the model statistics, such as the log-likelihood and degree of freedom, for the assessment of the goodness-of-fit of the fitted model. Is there any way that I can generate these statistics for the fitted model in R? Many thanks in advance! SC

Hi, I'm trying to fit a fixed effect (LSDV) panelmodel with R. I have a dataset with y as dependent, x1&x2 as indeps, t as time index and i as an id-variable for each individual. There are three observations for each individual (t=1, t=2, t=3). I want to try a simple regression, but with individual intercepts: ------------------------------------------------- # reading in some data ...

Hello there, I am using nlme() to fit a logistic mixed effect model on our data. The outcome variable is binary. I got the error when I wanted to add a group factor to my model. My initial model is as below: model.a <- nlme(response~ 1/(1 + exp( -intercept- u0 - slope*TIME - u1*TIME)), + fixed=intercept+slope~1, random= u0+u1~1 |studentID,