search for: 0.184

Is there a way to have printing data.frames with POSIXct to display milliseconds if digits.secs is set as a default? You can use the digits argument in print, such as print(df, digits = 3) to get the intended output, but I assumed it was done with the option digits.secs set. Tibbles by default do this printing, which is shown below, but I was unsure if digits.secs should affect printing

What do I need to do to fix this? [jonsmirl@smirl klibc-0.184]$ make make[1]: Entering directory `/home/dri/klibc-0.184/klibc' gcc -Wp,-MT,syscalls.nrs,-MD,./.syscalls.nrs.d -mregparm=3 -DREGPARM=3 -march=i386 -Os -g -falign-functions=0 -falign-jumps=0 -falign-loops=0 -nostdinc -iwithprefix include -D__KLIBC__ -DBITSIZE=32 -I../include/arch/i386 -I../include/bits32 -I../include

Hello I have a data set like below: plate.id well.id Group HYB rlt1 1 P1 A1 Control SKOV3hyb 0.190 2 P1 A2 Control SKOV3hyb 0.210 3 P1 A3 Control SKOV3hyb 0.205 4 P1 A4 Control SKOV3hyb 0.206 5 P1 A5 Control SKOV3hyb 0.184 385 P1 A1 ovca SKOV3hyb 0.184 386 P1 A2 ovca SKOV3hyb 0.229 387

Hi, I'm trying to build several SCL perl516 modules for using assp spamfilter. Some modules have dependencies which spend a lot of errors or can not be build on a x86_64 system. perl-Email-Valid-0.184 for example needs Win32::IPHelper and Win32::TieRegistry. If I build this rpm for standard perl510, the Win32 modules are not required. Why are theses dependencies only for perl516? Can I

If I have a table (we'll call it, "test") containing two columns (as below): i x1 x2 x3 x4 x5 y 0 1.125 0.232 7.160 0.0859 8.905 1.5563 7 0.920 0.268 8.804 0.0865 7.388 0.8976 15 0.835 0.271 8.108 0.0852 5.348 0.7482 22 1.000 0.237 6.370 0.0838 8.056 0.7160 29 1.150 0.192 6.441 0.0821 6.960 0.3130 37 0.990 0.202 5.154 0.0792 5.690 0.3617 44 0.840 0.184 5.896 0.0812 6.932 0.1139 58

Hi there, Everytime when I paste My R output in WORD, the columns couldn't line up nicely like they appear in R console. Is there a way to fix this problem? Thanks for any help! time n.risk n.event survival std.err lower 95% CI upper 95% CI 6 21 3 0.857 0.0764 0.707 1.000 7 17 1 0.807 0.0869 0.636 0.977 10 15 1

I currently work on a draft of an aquatic bioassessment. The conditions tested are the following: ER river water T dechlorinated water control 0.5 + 0.5mg / L of malate T + 1 dechlorinated water control + 1g / L of malate T ED dechlorinated water control SED + ER + river water sediment SED ED + sediment + water dechlorinated. It is the result of AChE in muscle (fillet of fish). The production of

Hi, all There are 62 samples in my data and I tested 3 times for each one, then I want to use ICC(intraclass correlation) from irr package to test the consistency among the tests. *combatexpdata_p[1:62] is the first text results and combatexpdata_p[63:124] * is the second one and *combatexpdata_p[125:186]* is the third. Here is the result:

Hello, I hesitate to call this a bug, because I could have forgotten something important, but the MarkowitzPortfolio example in fPortfolio does not work for me. Here's my code: > library(fPortfolio) > >xmpPortfolio("\nStart: Load monthly data set of returns > ") > data(berndtInvest) > # Exclude Date, Market and Interest Rate columns from data

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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,] 

Consider the following example (based on an example in Pat Altham's GLM notes) pyears <- scan() 18793 52407 10673 43248 5710 28612 2585 12663 1462 5317 deaths <- scan() 2 32 12 104 28 206 28 186 31 102 Smoke <- gl(2,1,10,labels=c("No","Yes")) Age <- gl(5,2,10,labels=c("35-44","45-54","55-64","65-74","75-84"),

Hello, I am trying to recursively append some data from multiple files into a common object For this, I am using in a loop NewObject <- rbind(NewObject,tempObject) For the first loop, obviously there is no NewObject ... so I wanted to do NewObject <- tempObject[0,] Now when it loops again I want to put the statement do "NewObject <- tempObject[0,]" inside a if statement

Dear friends, In R, the help of "bic.glm" tells the difference between postmean(the posterior mean of each coefficient from model averaging) and condpostmean(the posterior mean of each coefficient conditional on the variable being included in the model), But it's still unclear about the results explanations, and the artile of Rnews in 2005 on BMA still don't give more detail on

Hi everybody, I noticed a strange behavior when using loops versus apply() on a data frame. The example below "explicitly" computes a distance matrix given a dataset. When the dataset is a matrix, everything works fine. But when the dataset is a data.frame, the dist.for function written using nested loops will take a lot longer than the dist.apply ######## USING FOR ####### dist.for

Some help with how to re-label the vertical axis in a histogram would be appreciated. qplot(off.sc,weight=rel.freq,binwidth=.29,main="test Figure"+ylab("New from inside"))+ylab("New from outside")+ xlab("off.sc\nAggregated frequency plots for 17 equal intervals.") The code

Suharto, If you're interested in performance with subscripting, you might want to look at pqR (pqR-project.org). It has some substantial performance improvements for subscripting over R Core versions. This is especially true for the current development version of pqR (probably leading to a new release in about a month). You can look at a somewhat-stable snapshot of recent pqR development

Dear all R users, I am really struggling to determine the most appropriate lag order of ARIMA model. My understanding is that, as for MA [q] model the auto correlation coeff vanishes after q lag, it says the MA order of a ARIMA model, and for a AR[p] model partial autocorrelation vanishes after p lags it helps to determine the AR lag. And most appropriate model choosed by this argument gives

Hi, I have a Community (COM) composed of 6 species: A, B, C, D, E & F. The density of my Community is thus (Eq.1): dCOM = dA + dB + dC + dE + dF I would like to calculate and plot a linear regression between the density of each of my species and the density of the whole community (illustrating how the density of each species varies with variations of the whole community). For example, I would

days=Sys.Date()-1:70 price=abs(rnorm(70)) regular=rep(c(0,0,0,0,1,0,1,0,0,1),c(7,7,7,7,7,7,7,7,7,7)) y=data.frame(cbind(days,price,regular)) y is like days price regular 1 14990 0.16149463 0 2 14989 1.69519358 0 3 14988 1.57821998 0 4 14987 0.47614311 0 5 14986 0.87016180 0 6 14985 2.55679229 0 7 14984 0.89753533 0 the output I want: