similar to: Difference between R and SAS in Corcordance index in ordinal logistic regression

Dear community, I'm currently attempting to predict the occurence of an event (factor) having more than 2 levels with several continuous predictors. The model being ordinal, I was waiting the glm function to return several intercepts, which is not the case when looking to my results (I only have one intercept). I finally managed to perform an ordinal polytomous logisitc regression with the

Dear community, I am currently trying to fit an ordinal logistic regression model with the polr function. I often get the same error message : "attempt to find suitable starting values failed", for example with : require(MASS) data(iris) polr(Species~Sepal.Length+Sepal.Width+Petal.Length+Petal.Width,iris) (I know the response variable Species should be nominal but I do as levels

In polr.R the (several) functions gmin and fmin contain the code > theta <- beta[pc + 1L:q] > gamm <- c(-100, cumsum(c(theta[1L], exp(theta[-1L]))), 100) That's bad. There's no reason to suppose beta[pc+1L] is larger than -100 or that the cumulative sum is smaller than 100. For practical datasets those assumptions are frequently violated, causing the

Hi, when I generated a survfit() object, I can get number of patients at risk at various time points by using summary(): fit<-survfit(Surv(time,status)~class,data=mtdata) summary(fit) class=1 time n.risk n.event survival std.err lower 95% CI upper 95% CI 9.9 78 1 0.987 0.0127 0.963 1 41.5 77 1 0.974 0.0179 0.940 1 54.0 76

Well pointed out, Jim! It is infortunate that the documentation for options(digits=...) does not mention that these are *significant digits* and not *decimal places* (which is what Joshua seems to want): "?digits?: controls the number of digits to print when printing numeric values." On the face of it, printing the value "0,517" of 'ccc' looks like printing 4

R version 3.5.0 (2018-04-23) -- "Joy in Playing" Platform: x86_64-pc-linux-gnu (64-bit) options(digits=3) itemInfo <- structure(list("aaa" = c(1.39633732316667, 1.32598263816667, 1.11658324066667, 1.23651072616667, 1.05368679983333, 1.03100737383333, 0.9630728395, 0.7483865045, 0.620086646166667, 0.5411017985, 0.496397607833333, 0.459528044666667, 0.427877047833333,

Hi Joshua, Because there are no values in column ddd less than 1. itemInfo[3,"ddd"]<-0.3645372 itemInfo aaa bbb ccc ddd eee skill 1.396 6.225 0.517 5.775 2.497 predict 1.326 5.230 0.462 5.116 -2.673 waiting 1.117 4.948 NA 0.365 NA complex 1.237 4.170 0.220 4.713 5.642 novelty 1.054 4.005 0.442 4.260 2.076 creative 1.031 3.561 0.362 3.689

>>>>> Ted Harding >>>>> on Thu, 31 May 2018 07:10:32 +0100 writes: > Well pointed out, Jim! > It is infortunate that the documentation for options(digits=...) > does not mention that these are *significant digits* > and not *decimal places* (which is what Joshua seems to want): Since R 3.4.0 the help on ?options *does* say

Hello, my test.R file contains two huge arrays (>3000 entries), from which R needs to calculate the Pearson Correlation, if I look at the file the numbers look correct. if I run R R < test.R --no-save I see things like this: 0.723, 0.838, 1.002, 0.364, 0.357, 0.227, 0.982+ , 0.963, 0.535, 1.214, 1.270, 0.832, 1.033, 0.632, 2.482, 1.239, 0.743, 1.077, 0.962, 1.052, 1.075, 1.427, 1.395,

Dear list, I have the following matrix. How can I make the following plot? 1. The x-axis has index 1:7, and the first column is plotted against index 1, second against 2, and so on. 2. I want the points from the left upper conner including the antidiagonal to be plotted with col=2, and the rest with col=3 [,1] [,2] [,3] [,4] [,5] [,6] [,7] [1,] 0.589 0.857 0.923 0.944 0.954 0.963

mac osx 10.5.4 R 2.7.1 I have fit a model d<-lm(y~x) with an R^2 of 0.963 but when I issue the command abline(d) the line is below where it ought to be. Looks like the right slope, but not the right intercept. thanks -- Stephen Sefick Research Scientist Southeastern Natural Sciences Academy Let's not spend our time and resources thinking about things that are so little or so large

Dear R-Helpers, I've looked high and low for a function that provides frequencies, proportions and cumulative proportions side-by-side. Below is the table I need. Is there a function that already does it? Thanks, Bob > # Generate some test scores > myValues <- c(70:95) > Score <- ( sample( myValues, size=1000, replace=TRUE) ) > head(Score) [1] 77 71 81 88 83 93 > >

Hello, When evaluating different learning methods for a categorization problem with the (really useful!) caret package, I'm getting confusing results from the Kappa computation. The data is about 20,000 rows and a few dozen columns, and the categories are quite asymmetrical, 4.1% in one category and 95.9% in the other. When I train a ctree model as: model <- train(dat.dts,

I am performing a binary classification using a classification tree. Ironically, the data themselves are 2483 tree (real biological ones) locations as described by a suite of environmental variables (slope, soil moisture, radiation load, etc). I want to separate them from an equal number of random points. Doing eda on the data shows that there is substantial difference between the tree and random

Dear R-list members, Some months ago I wrote a message on the usage of gnls (nlme library) and here I come again. Let me give an example: I have a 10 year length-at-age data set of 10 fishes (see growth.dat at the end of this message) and I want to fit a von Bertalanffy growth model, Li= Linf*(1-exp(-k*(ti-t0))) where Li = length at age i, Linf= asymptotic length, k= curvature parameter, ti=

Dear list members, I am new to R and to the R-help list. I am trying to perform a mixed-model analysis using the lmer() function. I have a problem with the output anova table when using the anova() function on the lmer output object: I only get the numerator d.f., the sum of squares and the mean squares, but not the denominator d.f., F statistics and P values. Below is a sample output, following

Dear All- I have a dataset that is comprised of the following: doy yr mon day hr hgt1 hgt2 hgt3 co21 co22 co23 sig1 sig2 sig3 dif flag 244.02083 2005 09 01 00 2.6 9.5 17.8 375.665 373.737 373.227 3.698 1.107 0.963 -0.509 PRE 244.0625 2005 09 01 01 2.6 9.5 17.8 393.66 384.773 379.466 15.336 11.033 5.76 -5.307 PRE 244.10417 2005 09 01 02 2.6 9.5 17.8 411.162 397.866 387.755 6.835 5.61 6.728

On 2019/7/20 0:13, Michael S. Tsirkin wrote: > On Fri, Jul 19, 2019 at 03:31:29PM +0000, ? jiang wrote: >> On 2019/7/19 22:29, Jiang wrote: >>> On 2019/7/19 10:36, Jason Wang wrote: >>>> On 2019/7/18 ??10:43, Michael S. Tsirkin wrote: >>>>> On Thu, Jul 18, 2019 at 10:42:47AM -0400, Michael S. Tsirkin wrote: >>>>>> On Thu, Jul 18, 2019

On 2019/7/20 0:13, Michael S. Tsirkin wrote: > On Fri, Jul 19, 2019 at 03:31:29PM +0000, ? jiang wrote: >> On 2019/7/19 22:29, Jiang wrote: >>> On 2019/7/19 10:36, Jason Wang wrote: >>>> On 2019/7/18 ??10:43, Michael S. Tsirkin wrote: >>>>> On Thu, Jul 18, 2019 at 10:42:47AM -0400, Michael S. Tsirkin wrote: >>>>>> On Thu, Jul 18, 2019

On 2019/7/19 22:29, Jiang wrote: > > On 2019/7/19 10:36, Jason Wang wrote: >> >> On 2019/7/18 ??10:43, Michael S. Tsirkin wrote: >>> On Thu, Jul 18, 2019 at 10:42:47AM -0400, Michael S. Tsirkin wrote: >>>> On Thu, Jul 18, 2019 at 10:01:05PM +0800, Jason Wang wrote: >>>>> On 2019/7/18 ??9:04, Michael S. Tsirkin wrote: >>>>>> On