similar to: Fitting Multiple Univariate Distributions to Data

I have been using the ECDF function in the Hmisc package to produce cumulative distribution function plots. The problem is that for small datasets the steps "look bad" (not my characterization but from the client). Is there a way to get the same information but smoothed? I have tried the densityplot (lattice), which gives a smoothed line, but this does not give the cumulative density.

I have written a few different summary functions. I want to calculate the statistics by groups and I am having trouble getting the output as a dataframe. I have attached one example with a small dataset that calculates summary stats and percentiles, I have others that calculate upper confidence limits etc. I would like the output to be converted to a dataframe with one of the columns as the

I am looking to create what I would call a "simple variation" on the boxplot. What I would like to do is to be able to plot the upper and lower confidence limits as the "box" and the 10th and 90th percentile as the whiskers. What I have done is write the code to create a dataframe, the columns of which are the mean, sd, 10th percentile, 90th percentile, lower confidence limit

I am trying to create some plots of concentration versus depth. I want Depth on the Y axis and the concentrations on the X axis. I also need to plot error bars. The xYplot function in Hmisc is very nearly ideal but I have to put depth on the x-axis to get it to work. When I transpose the X and Y axes in the xYplot command, the error bars disappear (no surprise given the help file). It there a

Greetings, I am running a buch of wilcox tests and need to be able to rapidly export the results into a csv file. I have attached example code as well as my attempts to get what I need. I have tried unlist,cbind,rbind etc but I am obvously missing something simple. FYI I am actually running about 50 WRS tests per dataset, this is just an example. Thanks 10^6 Mike AKCCR <-

I am debugging some code and found a function that returns and error most of the time. I have issolated the problem to when it raises an argument to the 1/3 power but for the life of me I can not figure out why it is not working. i have gone through the FAQs and have found nothing (not to say I might have missed something). I am highly embarrased with my inability find the problem (my face is

I am using R for environmental forensics (determination of the sources and/or groupings in mixtures of organic chemicals in the field). The goal is to determine in there are groups of samples with similar/dissimilar compositions, and to assign samples to a potential source or a mixture of sources based on the composition (unmixing and source allocation). Typically there are 10 to 50 chemicals that

I was preparing an e-mail for the help list and ran across a quandary. When asking for help it is useful to include the code/data so others can run your code and test it. I was running code on a data frame and wanted to include a small version of the data frame. The data frame was based on experimental data. What is the best way to do this? I didn't want to send an attachment so a wrote code

I need to do a sample size calculation to determine the number of audits required. The results of an audit will be: 1) OK 2) Minor variances 3) Multiple variances 4) Severe variances We want to know the sample size required to determine the proportions in each category within say 5% with a confidence of say 80% (specific values to be determined). I have used the test of proportions before but

Dear All, I would be grateful if you can help me. My problem is the following: I have a data set like: ID time X1 X2 1 1 x111 x211 1 2 x112 x212 2 1 x121 x221 2 2 x122 x222 2 3 x123 x223 where X1 and X2 are 2 covariates and "time" is the time of observation and ID indicates the

I have searched the archives and instructions high and low but have not found what I need. I have a dataframe named Data with columns: AdjResND0 - the numeric result Parameter - the classification (chemical name) Sort - the order I want the chemical names to appear, with leading zeros so all are the same length Client.Name - the sample name I am trying to generate a series of 1 page barcharts,

I am trying to get the same text printed on each page of a multi-page series of bar charts. The text need to appear in the upper left-hand corner of the page, outside of the plot area. A watermark might be the closest analogy to what I am after This is what I have so far: PData <- na.omit(subset(TData,Matrix == "Product")) barchart(AdjResND0 ~ reorder(Compound, Sort) | Label ,

I need to do a sample size calculation to determine the number of audits required. The results of an audit will be: 1) OK 2) Minor variances 3) Multiple variances 4) Severe variances We want to know the sample size required to determine the proportions in each category within say 5% with a confidence of say 80% (specific values to be determined). I have used the test of proportions before but

I am using lattice to make figures as pdfs: trellis.device(device = "pdf",file = "Figure6.pdf",color = FALSE) I need to specify some blank space on the left-hand margins (the pages will be bound so we need about 0.5 inch)). I have tried a number of solutions but none seems to work (e.g. par.set). Can this be done when initiating the plotting device? Or is the some other way

I have data set with binary responses. I would like to conduct polychoric principal component analysis (pPCA). I know there are several packages used in PCA but I could not find one that directly estimate pPCA and graph the individuals and variables maps. I will appreciate any help that expand these reproducible scripts. #How to conduct polychoric principal component analysis pPCA using #either

Greetings, We are performing a meta-analysis of mink pup survival data versus chemical concentration. We have modeled percent survival successfully using nls as shown below and the plot. What we need to do is construct a confidence interval on the concentration at which we get 50% survival (aka the EC50, although we may want other percent survivals in the future). My first question is, what seems

{Note the DATE ! this message bounced ... because it was sent to R-announce which was definitely the wrong list anyway. MM - your list maintainer } Dear R-Team I have installed R version 0.990 and the foreign package under Windows NT.. Whilst lookup.xport() works as it should, read.xport() crashes reporting an "access error" as well for larger datasets as also for small

Dear expeRts, I collect some lab specific functions for a package. Some of this functions need initial data (ini files written in R-code). My question is: Where is the place in the package structure for such files; how to load the files? I think something like: source(paste(R.home(),"/library/__pkg__/data/__.ini.R", sep="")) looks a bit clumsy. I haven't find something

In response to a feature request for cpanel to have native support for dovecot: Rudimentary support was added in 11.23. Full support for Dovecot will be available in 11.24. -- Marshal Newrock 517-679-0699 x223 FreedomBI, LLC - http://www.freedombi.com -------------- next part -------------- A non-text attachment was scrubbed... Name: signature.asc Type: application/pgp-signature Size: 189

Dear List, I have a theoretical question related to epidemiological data analysis: If the treatment status (tx = 0,1) changes over time for the patients in a non-randomized cohort, is there a way to estimate the treatment effect? (i.e., after joining the study, some patients may have to wait for a period of time before receiving the treatment, i.e., the situation of patient with id == 2 for the