similar to: chisq.test with simulate.p.value=TRUE (PR#13292)

I'm using R1.7.0 runing with Win XP. Thanks, ...Tao ???????????????????????????????????????????????????????? >x [,1] [,2] [1,] 149 151 [2,] 1 8 >t(x) [,1] [,2] [1,] 149 1 [2,] 151 8 >chisq.test(x, simulate.p.value=T, B=100000) Pearson's Chi-squared test with simulated p-value (based on 1e+05 replicates) data: x X-squared = 5.2001, df =

Hello everybody, I'm seeing some strange behavior on R 1.8.1 on Intel/Linux compiled with gcc 3.2.2. The p-value calculated from the chisq.test function is incorrect for some input values: > chisq.test(matrix(c(0, 1, 1, 12555), 2, 2), simulate.p.value=TRUE) Pearson's Chi-squared test with simulated p-value (based on 2000 replicates) data: matrix(c(0, 1, 1,

Dear List, If any of observed and/or expected data has less than 5 frequencies, then chisq.test (Pearson's Chi-squared Test for Count Data from package:stats) gives warning messages. For example, x<-c(10, 14, 10, 11, 11, 7, 8, 4, 1, 4, 4, 2, 1, 1, 2, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1) y<-c(9.13112391745095, 13.1626482033341, 12.6623267638188, 11.0130706413029, 9.16415925139016,

I have been tinkering with mosaicplot() and friends as a way of learning R. As part of this, I've written a pair.table() method for mosaic matrices, and would like to extend mosaicplot to work with loglin and logln (MASS) objects. I'm using R 1.4.0 on Win 98. I've been trying to figure out the formula interface, and think there's a bug, but not sure how to find it, yet alone fix

Hi I am running chisq as below and getting a warning. Can anyone tell me the significance or the warning? > chisq.test(c(10 ,4 ,2 ,6 ,5 ,3 ,4 ,4 ,6 ,3 ,2 ,2 ,2 ,4 ,7 ,10 ,0 ,6 ,19 ,3 ,2 ,7 ,2 ,2 ,2 ,1 ,32 ,2 ,3 ,10 ,1 ,3 ,9 ,4 ,10 ,2 ,2 ,4 ,5 ,7 ,6 ,3 ,7 ,4 ,3 ,3 ,7 ,1 ,4 ,2 ,2 ,3 ,3 ,5 ,5 ,4 ), p =c(0.01704142 ,0.017988166 ,0.018224852 ,0.017751479 ,0.017988166 ,0.018224852 ,0.017278107

Full_Name: nobody Version: 2.2.0 OS: any Submission from: (NULL) (219.66.34.183) 2 x 2 table, such as > x [,1] [,2] [1,] 10 12 [2,] 11 13 > chisq.test(x) Pearson's Chi-squared test with Yates' continuity correction data: x X-squared = 0.0732, df = 1, p-value = 0.7868 but, X-squared = 0.0732 is over corrected. when abs(a*d-b*c) <= sum(a,b,c,d), chisq.value

Reading "R Internals" made me believe that R_UnboundValue was a placeholder that would be skipped over in variable lookup. viz. the section of R Internals "Hash tables" says "items are not actually deleted but have their value set to R_UnboundValue.", which seems to align with what I read in envir.c. So, I reasoned, if I have a function that returns R_UnboundValue,

I am getting "Chi-squared approximation may be incorrect in: chisq.test(x)" with the data bleow. Frequency distribution of number of male offspring in families of size 5. Number of Male Offspring N 0 518 1 2245 2 4621 3 4753 4 2476 5

I'm trying to find a way to change the font size in a mosaic plot (the grid version, not the base graphics one). Here's an example to demonstrate: #Basic plot library(vcd) mosaic(HairEyeColor, shade = TRUE) #Bad first guess: this stops the default cell colouring, and doesn't change the font size mosaic(HairEyeColor, shade = TRUE, gp=gpar(fontsize=16)) #This successfully changes

I am using R to teach, and here are a couple of things that I thought would work didn't work. 1. I noticed the utility data(***,package=***) recently and like it very much, but unless I type in the whole word "package" I'll get an error in 1.4.0. For example, data(cats,package=MASS) works fine but data(cats,pac=MASS) doesn't. 2. drop1 doesn't seem to be as smart as

Hi, I have a text mining project and currently I am working on feature generation/selection part. My plan is selecting a set of words or word combinations which have better discriminant capability than other words in telling the group id's (2 classes in this case) for a dataset which has 2,000,000 documents. One approach is using "contrast-set association rule mining" while the

Hello! What kind of calculation perform 'chisq.test', if its argument is a matrix? Thanks for any suggestion! ------------------------------------------------------------ Sincerely yours. Dr. Alessandro Semeria Tel. +39 544 536811 Models and Simulation Lab of Fax. +39 544 538663 The Environment Research Center - Montecatini

Hello, I am trying to fit gamma, negative exponential and inverse power functions to a dataset, and then test whether the fit of each curve is good. To do this I have been advised to calculate predicted values for bins of data (I have grouped a continuous range of distances into 1km bins), and then apply a chi-squared test. Example: > data <- data.frame(distance=c(1,2,3,4,5,6,7),

Dear R-helpers, Suppose I have dataset like this below: data(HairEyeColor) dfHEC <- as.data.frame(as.table(HairEyeColor)) my.dfHEC <- data.frame(Hair=rep(dfHEC$Hair,dfHEC$Freq), Eye=rep(dfHEC$Eye,dfHEC$Freq), Sex=rep(dfHEC$Sex,dfHEC$Freq)) my.dfHEC my.dfHEC$Hair my.dfHEC$Eye my.dfHEC$Sex and I know all levels for Hair, Eye and Sex. In my case, I

Hi, This report deals with p-values coming from chisq.test using the simulate.p=TRUE option. The issue is numerical accuracy and was brought up in previous bug reports 3486 and 3896. The bug was considered fixed but apparently was only mostly fixed. Just the typical problem of two values that are mathematically equal not ending up numerically equivalent. Consider this series of three 2x2

My question is based on an example provided in the following: Referencing: Statistics with R Vincent Zoonekynd <zoonek at math.jussieu.fr> 6th January 2007 URL: http://zoonek2.free.fr/UNIX/48_R/all.html data(HairEyeColor) a <- as.table( apply(HairEyeColor, c(1,2), sum) ) # Provided Example barplot(a, beside = TRUE, legend.text = attr(a, "dimnames")$Hair) # I

I'm looking for a way to generalize the calculation of (log) odds ratios for 2 x 2 x {strata} frequency tables in vcd::oddsratio() to R x C x {strata} tables. For an R x C table, F, odds ratios can be defined in several ways; one simple way, particularly for tables with ordered factors, is to calculate the set of continuation odds ratios, based on the (R-1)x(C-1) set of 2x2 tables with

I was asked by my boss to do an analysis on a large data set, and I am trying to convince him to let me use R rather than SPSS. I think Sweave could make my life much much easier. To get me a little closer to this goal, I ran my analysis through R and SPSS and compared the resulting values. In all but one case, they were the same. Given the matrix [,1] [,2] [1,] 110 358 [2,] 71 312 [3,]

Two proposals for mosaicplot(): - The argument "sub" should not be ignored. Example: mosaicplot( HairEyeColor, sub = 'test of sub' ) - To be able to discern also longer axis labels the argument "las" or par(las=2) should not be ignored. Example: mosaicplot( HairEyeColor, las=2 ) Thanks Wolfram

Hello, I am trying to use the extended assocplot() function: assoc(), from vcd package. Trouble is that it cannot even run its own examples on my installation. I get this output: $> example(assoc) assoc> data("HairEyeColor") assoc> (x <- margin.table(HairEyeColor, c(1, 2))) Eye Hair Brown Blue Hazel Green Black 68 20 15 5 Brown 119 84 54