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I am trying to use t.test on the following data: date type INTERVAL nCASES MTF SDF MTO SDO nFST MF nOBS MO MB BIASCV BIASEV ME MAE RMSE CRCF 2001-06-15 avn GE1.00 4385 0.246 0.300 1.502 0.556 1367 1.373 4385 1.502 1.471 0.285 0.164 -1.256 1.266 1.399 0.056 2001-06-15 avn

I was wondering if anyone could help me with this, simple problem. I am essentially following the example on Hadley's webpage (http://had.co.nz/ggplot2/geom_errorbar.html), but it still doesn't make any sense to me. df <- data.frame(trt = factor(c("intact", "intact", "removed", "removed")), coon = c(0.093, 0.06, 0.057, 0.09), group =

I have a table like the following. I want to fit Cm to Vm like this: Cm ~ Cl+Q1*b1*38.67*exp(-b1*(Vm-Vp1)*0.03867)/(1+exp(-b1*(Vm-Vp1)*0.03867))^2+Q2*b2*38.67*exp(-b2*(Vm-Vp2)*0.03867)/(1+exp(-b2*(Vm-Vp2)*0.03867))^2 I use nls, with start=list(Q1=2e-3, b1=1, Vp1=-25, Q2=3e-3, b2=1, Vp2=200). But I always get 'singlular gradient' error like this. But in SigmaPlot I can get the result. How

Hi there, I am doing multiple comparisons for data that is not normally distributed. For this purpose I tried both functions kruskal{agricolae} and kruskalmc{pgirmess}. It confuses me that these functions do not yield the same results although they are doing the same thing, don't they? Can anyone tell my why this happens and which function I can trust? kruskalmc() tells me that there are no

On Tue, Jul 30, 2019 at 11:54:53AM -0400, Michael S. Tsirkin wrote: > On Tue, Jul 30, 2019 at 05:43:29PM +0200, Stefano Garzarella wrote: > > This series tries to increase the throughput of virtio-vsock with slight > > changes. > > While I was testing the v2 of this series I discovered an huge use of memory, > > so I added patch 1 to mitigate this issue. I put it in this

In that case, I can't work out why the first model fails but not the second. I would start looking at "Data" to see what it contains. if: object2 <- polr(Inc ~ Training ,Data,Hess = T,method = "logistic" ) works, the problem may be with the "Adopt" variable. Jim On Tue, Mar 20, 2018 at 10:55 AM, Willy Byamungu <wmulimbi at email.uark.edu> wrote: >

I am trying to learn how to format Ascii data files for scan or read into R. Precisely for a quickie project, I found some code (at end of this email) to do exactly what I need: To cluster and graph a dendrogram from package (stats). I am stuck on how to format a text file to run the script. I looked at the dataset USArrests (which would be replaced by my data and labels) using UltraEdit. That

Dear All, I'me having (much) trouble understanding why it happened and answering a referee's comment to part of a submitted manuscript. I've tried to google for help but... I'm really confident that although this is a R-Help list someone can help me! I used R to do an ANCOVA w/ RNA/DNA as the dep var, sl as the indep var and gut (a factor w/ levels: prey and empty) as the

Hi, I have a set of data (total number of record = 144,122), and I would like to use gamma-glm with log link to set up a model. IC is number of records IL is paid amount The table below shows that I have 30.578% of the data in the level of "1 - 1000" paid amount 20.320% of the data in the level of "1001 - 2000" paid amount and so on My question is could i use the whole data

This is what my data looks like DOC TOC TKN RM119mFeb-06 1 2 3 RM61mFeb-06 2 4 6 I have this both in a .csv and .txt I have read this in with read.csv("chemodr.csv", header=T) and this is what I get X dAmon DN.N Nitrite.N DOC OP P TKN TOC 1 RM215mFeb-06 0.000 0.1300 0.0000 2.5

I fit the following model using glmmPQL from MASS: fit.glmmPQL <- glmmPQL(ifelse(class=="Disease",1,0)~age+x1+x2,random=~1|subject,family=binomial) summary(fit.glmmPQL) The response is paired (pairing denoted by subject), although some subjects only have one response. Also, there is a perfect positive correlation between the paired responses. x1 and x2 can and do differ within each

Hi r-users,   I would like to extract the data that match.  Attached is my data: I'm interested in matchind the value in column 'intg' with value in column 'rand_no' > cbind(z=z,intg=dd,rand_no = rr)             z  intg rand_no    [1,]  0.00 0.000   0.001    [2,]  0.01 0.000   0.002    [3,]  0.02 0.000   0.002    [4,]  0.03 0.000   0.003    [5,]  0.04 0.000   0.003    [6,] 

Odd behaviour of function cor() in R-2.10.1-64bit-Unix In a dataset with 1366 patients and 244 clinical variables Spearman's Rho was calculated for some fatty acids and BMI and came over something rather odd: R seems to calculate Rho differently on 2.10.1-64bit-Unix and 2.9.0-32bit-Windows when I calculate the complete (244x244) correlation matrix and then pick out the values I am

Hi, There seems to be a problem with the timer resolution on x86_64. This is clear in ping results - I don't know if it's just a ping problem or if it manifests elsewhere as well. It does also affect mtr and traceroute times. I guess it's more a kernel issue than a CentOS problem, but is anyone else seeing the same? Ping results have a resolution of 10ms - so a ping <10ms

On Wed, Jul 17, 2019 at 01:30:25PM +0200, Stefano Garzarella wrote: > This series tries to increase the throughput of virtio-vsock with slight > changes. > While I was testing the v2 of this series I discovered an huge use of memory, > so I added patch 1 to mitigate this issue. I put it in this series in order > to better track the performance trends. Series: Acked-by: Michael S.

On Tue, Jul 30, 2019 at 05:43:29PM +0200, Stefano Garzarella wrote: > This series tries to increase the throughput of virtio-vsock with slight > changes. > While I was testing the v2 of this series I discovered an huge use of memory, > so I added patch 1 to mitigate this issue. I put it in this series in order > to better track the performance trends. > > v5: > - rebased

This series tries to increase the throughput of virtio-vsock with slight changes. While I was testing the v2 of this series I discovered an huge use of memory, so I added patch 1 to mitigate this issue. I put it in this series in order to better track the performance trends. v5: - rebased all patches on net-next - added Stefan's R-b and Michael's A-b v4:

This series tries to increase the throughput of virtio-vsock with slight changes. While I was testing the v2 of this series I discovered an huge use of memory, so I added patch 1 to mitigate this issue. I put it in this series in order to better track the performance trends. v5: - rebased all patches on net-next - added Stefan's R-b and Michael's A-b v4:

OK, Let's try this again! Here is the reproducible script; it is long because I had to copy the panel dataset here. My question is related to systemfit; I don't know how to get the result for the entire panel. #Reproducible script Empdata<- read.csv("/Users/ngwinuiazenui/Documents/UPLOADemp.csv") View(Empdata) install.packages("systemfit")

Dear all Please help me with correct syntax of predict.nlme. I would like to predict from nlme object for new data. I used predict(fit.nlme6, data=newdata) but I have always got fitted values, no matter how I changed newdata. I have > summary(fit.nlme6) Nonlinear mixed-effects model fit by maximum likelihood Model: konverze ~ SSfpl(tepl, A, B, xmid, scal) Data: limity.gr AIC