search for: 0.358

...and i'm getting all cases which are true for above condition and get the information how many cases match, too. The vector's are in a attached data.frame. FAKTOR30[FAKTOR30 > 0.234] ................... [102193] 0.352 0.352 0.288 0.354 0.352 0.358 0.352 0.352 0.311 0.370 0.352 0.336 [102205] 0.352 0.274 0.352 0.405 0.354 0.352 0.352 0.352 0.352 0.352 0.352 0.340 [102217] 0.352 0.352

Ronaldo, Further to my previous posting on your Glycogen nested aov model. Having read Douglas Bates' response and Reflected on his lmer analysis output of your aov nested model example as given.The Glycogen treatment has to be a Fixed Effect.If a 'treatment' isn't a Fixed Effect what is ? If Douglas Bates' lmer model is modified to treat Glycogen Treatment as a purely

I have a data frame, lets call it dat, with 3 columns ( mc, yr, ret) which represent market cap, year, and return. mc is a factor, mc, and ret are real numbers. I want to add a column to the data calculated as follows. For each year, I want to split the data by mc decile, then calculate the mean ret within that mc decile, and finally subtract that year's decile mean from the raw return. Then

I am trying to it a particular nonlinear model common in Soil Science to moisture release data from soil. I have written the function as shown below according to the logist example in Ch8 of Pinheiro & Bates. I am getting the following error (R version 2.1.1) *Error in qr(attr(rhs, "gradient")) : NA/NaN/Inf in foreign function call (arg 1)* Below is the function and data. /#

Dear R-helpers, I'm stuck with a little problem that surely has an easy solution but I can't think of a way to solve it. I'd really appreciate any help you can offer me! I'll provide a small example. Given a dataframe data.txt that looks like this: ID freq Var Var_mean Ratio_mean Var_median Ratio_median Var_sum Ratio_min Var_max Ratio_max Var_min

Hi, In my analysis of impacts of insecticide-treated bednets on malaria, I look at the relationship between malaria incidence and mosquito behaviors. The condensed data set is copied here. Ordinary regression (lm) shows that Incidence was negatively related to Mortality. This makes sense because the latter reflected the strength of killing mosquitoes by insecticide-treated nets. Since the

A couple weeks ago I posted a message on this topic to r-help, the response was that this seemed like odd behavior, and that I ought to post it to one of the developer lists. I posted to r-sig-mixed-models, but didn't get any response. So, with good intentions, I decided to try posting once more, but to this more general list. The goal is (1) FYI, to make you aware of this issue, in case it

Dear all, I am attempting to explain patterns of arthropod family richness (count data) using a regression model. It seems to be able to do a pretty good job as an explanatory model (i.e. demonstrating relationships between dependent and independent variables), but it has systematic problems as a predictive model: It is biased high at low observed values of family richness and biased low at

I'd like to compare two models which were fitted using gls, however I'm having trouble interpreting the results of gls. If any of you could offer me some advice, I'd greatly appreciate it. Short explanation of models: These two models have the same fixed-effects structure (two independent, linear effects), and differ only in that the second model includes a corExp structure for

Hello, I am a very new R user and not a statistician so please excuse any over explanation, I'm just trying to be as clear as possible. I have performed a cross correlation of two time series (my columns) in a single data setusing: ccf(ts(A[rows,columnX]),(A[rows,columnY]), lag=NULL, type="correlation",plot=F) I?am able to get the results (for example): Autocorrelations of

On Wed, Jun 10, 2020 at 06:18:32PM +0200, Eugenio Perez Martin wrote: > On Wed, Jun 10, 2020 at 5:13 PM Michael S. Tsirkin <mst at redhat.com> wrote: > > > > On Wed, Jun 10, 2020 at 02:37:50PM +0200, Eugenio Perez Martin wrote: > > > > +/* This function returns a value > 0 if a descriptor was found, or 0 if none were found. > > > > + * A negative

This is a summary and extension of the thread "GLMM (lme4) vs. glmmPQL output" http://maths.newcastle.edu.au/~rking/R/help/04/01/0180.html In the new revision (#Version: 0.4-7) of lme4 the standard errors are close to those of the 4 other methods. Thanks to Douglas Bates, Saikat DebRoy for the revision, and to G?ran Brostr?m who run a simulation. In response to my first posting, Prof.

I want to compare the following two models in AIC (Treat, Spotter are categorial, p is pressure, Pain is continuous) PainW.lme<-lme(Pain~p+Treat*Spotter,data=saw,random=~p|Pat, weights=varPower(form=~Pain)) # AIC= -448 Pain.lme<-lme(Pain~p+Treat*Spotter,data=saw,random=~p|Pat) #AIC = -19.7 Note the huge differences in AIC, and the estimated power of 6. A plot of the residual

On Tue, Jun 16, 2020 at 05:23:43PM +0200, Eugenio Perez Martin wrote: > On Mon, Jun 15, 2020 at 6:05 PM Eugenio P??rez <eperezma at redhat.com> wrote: > > > > On Thu, 2020-06-11 at 07:30 -0400, Michael S. Tsirkin wrote: > > > On Wed, Jun 10, 2020 at 06:18:32PM +0200, Eugenio Perez Martin wrote: > > > > On Wed, Jun 10, 2020 at 5:13 PM Michael S. Tsirkin

I have a data matrix with genes as columns and samples as rows. I want to create all possible gene ratios.Is there an elegant and fast way to do it in R and write it to a dataframe? Thanks for any help. Som. -- View this message in context: http://r.789695.n4.nabble.com/Calculating-all-possible-ratios-tp4627405.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML

Hi all, I'm seeing this failure on my PPC G4 box running TOT with llvm-gcc 4.2. Is anyone else seeing this? I'm sure it's related to the byval stuff that's recently gone into LLVM. I'm attaching the output of this command: $ llvm-gcc -emit-llvm -O3 -S -o - -emit-llvm /Users/wendling/llvm/ llvm.src/test/CFrontend/2008-01-25-ByValReadNone.c As you can see in it, there

... and the mailing list is picky about attachments... whatever you attached did not conform to the stringent requirements mentioned in the Posting Guide. Pasting the code right into the email is usually safest, though you DO have to post using plain text (as the Posting Guide indicates) or your code may get mangled by the automatic html format removal. On May 15, 2018 7:04:31 AM PDT, Bert Gunter

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")

Unless there is good reason not to, always cc the list -- there are lots of smarter folks than I on it who can help. I may or may not have time to look at this. Hopefully someone else will. -- Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip

Sadly you failed to set your email program to send plain text and the data is corrupted at my end. I also think you need to reduce the size of the data set... the intent here is to increase your understanding, not debug your particular analysis. I will say that I am having a very challenging time understanding what you are trying to accomplish though. What are the equations that you think need