similar to: Optical Mark Recognition

Hi All, I'm trying to create two side-by-side contour plots with one legend by modifying the code found here: http://wiki.cbr.washington.edu/qerm/sites/qerm/images/b/bb/Example_4-panel_v1a.R I've been able to set up the other two functions called in the code, but I can't find reference to print.letterTrevor.R anywhere other than the page linked above. I've searched all the help

Hello! I'm interested in getting a Chinese optical character recognition program to run under wine. http://www.twinbridge.com/Products/SharpEye/ocr.html According to the web site, it may run on Windows 95 as well as the old Windows 3. Is it therefore safe to assume that it will run under wine? Surely it should be able to handle anything that can run on Windows 3 right? Any advice will

Dear R saviors, kindly address to this problem, I would really appreciate any takers. I am trying to resolve this issue of IMR in clustered (multilevel) cross-sectional panel data for more than two months now,. The characteristics of my dataset are as follows: - some 900 000 individuals - total of 60 countries - cross-sectional time series at the country level max 10 years, not all

Hello, I have a problem with using replace() to convert a vector of dates from yyyy-mm-dd to julian date. For example, I type replace(x,2004-05-14,134) and I receive an error: Error in `[<-.data.frame`(`*tmp*`, list, value = 134) : new columns would leave holes after existing columns If I can successfully convert, I have a script that will convert all of the dates in

Hi Jim, Thanks for your help, I really appreciate it. Perhaps I'm misunderstanding, but does this formula run different ajustment values for this function? logit(p = doc$value, adjust = 0.025) I'm looking to plot the p-values of different adjustment values. Thanks so much, Kirsten On Wed, Jul 12, 2017 at 8:49 PM, Jim Lemon <drjimlemon at gmail.com> wrote: > Hi Kirsten,

Hi Ben, That's exactly right! Except for each set it's the sample population that is 400, 800 or 300. I want to take 3 samples, each of 100, where only the population differs. I can do this separately, but I'm having trouble putting them all on the same graph. I'd like to have sample on the x axis (1-300) and estimate on the y axis. I want to show how population affects the

Not a reproducible example, so a bit of guessing here, but a) don't try to assign results to variables inside the ifelse. That is, remove all the single-equals signs and "test" variables. If you really need to conditionally assign variables then use "if"... but chances are good you don't need that. b) "closure" is effectively another word

Dear R experts, I want to plot a line chart with another secondary axis placed right to the standard secondary axis which one can access with the axis command, so that the data lines are seen in the same plot. Is there any way to do this in R? Many thanks, Kirsten.

Hi Kirsten, Perhaps this will help: set.seed(3) kmdf<-data.frame(group=rep(1:4,each=20), prop=c(runif(20,0.25,1),runif(20,0.2,0.92), runif(20,0.15,0.84),runif(20,0.1,0.77))) km.glm<-glm(prop~group,kmdf,family=quasibinomial(link="logit")) summary(km.glm) pval<-0.00845 padjs<-NA npadj<-1 # assume you have five comparisons in this family for(method in p.adjust.methods) {

Hi Kirsten, I can run your example code but I can't quite follow your division of sampling. Can you restate the the task? Below is what I think you are asking for, but I have the feeling I may be off the mark. Set A: 400 samples, draw 100 in range of 5 to 15 Set B: 800 samples, draw 100 in range of 5 to 15 Set C: 300 samples, draw 100 in range of 5 to 15 Ben > On Aug 5, 2017, at

Hi Caitlin and Ben, Thanks for your responses! My issue is that I'd like to create one continuous line, rather than 3 lines overlayed. The code I've attached works for a population of 400 and samples 100 times. I'd like to extend this to 300 samples and 3 populations. So, the x-axis would range from 0-300 samples. What I'm having trouble with is finding a way to change the

Hello everyone, I have a .csv file with the following format: uniqueID SubjectID Distance_miles Tag 1 1001 5.5 3 2 1001 7 1 3 1001 6.5 1 4 1001 5 1 5 1002

I have a researcher who is consistently get the warning message: In max(i) : no non-missing arguments to max; returning -Inf Best as I can tell the code is working properly and the output is as expected. I would like some help in understanding why he is getting this error message and what its implications are. I have his code. Sincerely, Kirsten Miles Support Specialist Research Computing Lab

Hello! I have measurements (length and volume) of fish collected in two years. I want to know if the the relationship between length and volume is the same for both years. The number of fish measured is different for each year. I don't know whether lm or aov is more appropriate to use. Here are the two output options: Call: lm(formula = Volume ~ Length * Year) Residuals: Min 1Q

Hi I have a stata data set (.dta file) of size 600 MB, I need to import it in R and do a 2SLS multilevel analysis on the data set. I would eb grateful if help is provided for the first part of how to import this big file from Stata to R and then how to open the imported Stata file in R? Kindly help Thanks in advance -- Dr.Saurav Pathak PhD, Univ.of.Florida Mechanical Engineering Doctoral

When adding a trend line to a scatterplot (e.g. abline (90,4,col="red"), I believe the "90" is the intercept and "4" is the slope. How do I determine the intercept and slope for the abline command? Kristopher R. Deininger Management Strategy & Entrepreneurship PhD Student 2012 Robert H. Smith School of Business University of Maryland 3330L Van Munching Hall

Dovecot version: 2.2.15 Tinycdb: 0.78 I'm attempting to compile dovecot --with-cdb, but keep getting into a problem with cdb: ======================== libtool: link: gcc -std=gnu99 -g -O2 -Wall -W -Wmissing-prototypes -Wmissing-declarations -Wpointer-arith -Wchar-subscripts -Wformat=2 -Wbad-function-cast -fno-builtin-strftime -Wstrict-aliasing=2 -Wl,--as-needed -o .libs/anvil main.o

I have so far used the following command glm(formula = s ~ age + gender + gemedu + gemhinc + es_gdppc + imf_pop + estbbo_m, family = binomial(link = "probit")) My question is 1. How do i discard the non significant selection variables (one out of the seven variables above is non-significant) and calculate the Inverse Mills Ratio of the significant variables 2. I need the inverse

Hello all, I have a data set where the response variable is the percent cover of a specific plant (represented in cover classes 0,1,2,3,4,5, or 6). This data set has a lot of zeros (plots where the plant was not present). I am trying to model cover class of the plant as a function of both total nitrogen and shrub cover. After quite a bit of research I have come across a conditional approach

Hey everyone, I'm working on a contour plot depicting asymptomatic prevalence at varying durations of infectiousness and force of infection. I've been able to work everything out except for this one - my legend title keeps getting cut off. Here's what I have: filled.contour(x=seq(2,30,length.out=nrow(asym_matrix)), y=seq(1,2,length.out=ncol(asym_matrix)), asym_matrix, color =