similar to: restore NAs in residuals

Dear r-users,   I have saved data in word pad.  I would like to extract certain part of data only, for example   19710629 080000(PARTIAL) 39.3 at interval beginning 19701126 010326 19720629 080000(PARTIAL) 33.8 at interval beginning 19720517 144507 19730629 080000(PARTIAL) 32.2 at interval beginning 19720910 135747   and so on...   The original data set are given below:      

Dear R users, I just join this forum a few minutes ago. My friend recommend this forum to me.   I have data in excel csv. My problem is I would like to extract some number, for example as highlighted below;   Year Ending           Maximum Value (Rain mm)  Gap from 19710509 090000 to 19710607 080000 of   28.96 Days 19710629 080000(PARTIAL)       39.3 at interval beginning 19701126 010326  Gap from

I encounter a statistic problem about correlation. I use R to test wether two variables are correlated or not. (pearson correlation) cor.test(x,y) give a p=5.87.... Because the x, y is not normal distributed (qqplot indicate that) I also perform (spearman rank correlation) cor.test(x,y,method="spearman") give a very significant result p<10e-4

Hi, I am trying to find m breakpoints of a linear regression model. I used the segmented package. It works fine for small number of predicators and breakpoints.(3 r.v. 3 points). However, my model has 14 variables it even would not work even for just one breakpoints!. The error message is always estimated breakpoints are out of range. Since my problem is time related problem. So I

I have a 5.5GB file, mostly sparse. Tar performs far[!] better than rsync. I have no ideas yet, so just an FYI as to current state. FreeBSD 8.1 i386 zfs Yes, I know the blocks used differs but don't know why yet, could be just how zfs does things or related to the large amount of sparseness. There are no media errors, CPU/IO load or anything like that and the source and dest paths are on the

Hello, I need help getting two data sets to merge. The structure of my two data sets are: > str(bcusip) 'data.frame': 1391 obs. of 3 variables: $ bond_id : Factor w/ 1391 levels "AAGH","AAGI",..: 1 2 3 4 5 6 $ Freq : num 41361 4126 5206 10125 45536 ... $ CUSIP_ID: Factor w/ 1391 levels "00184AAC9","00184AAF2",..: > str(bdescr)

Hallo, I am totally confused why Excel and R give me totally different regression results for the data below. If you know the solution, please enlighten me. In Excel I used LINEST() and Data>Data Analysis>Regression and both (fortunately) gave the same result. The coefficients were: /b0=1.16, b1=0.957, b2=0.024, R2=0.0027, adjusted R2=-0.017/ In R I used

I don't understand which is the problem Could you help me please? Thanks in advance Marta > str(data_indiciN2) 'data.frame': 200 obs. of 36 variables: $ gruppo: Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 2 2 2 ... $ I001N2: num 19.32 8.22 28.35 7.24 14.7 ... $ I002N2: num 2.92 2.54 0.11 1.6 7.12 ... $ I003N2: num -22.362 -0.222 -19.291

Dear R developers, I have encountered strange behaviour of fitdistr for gamma in recent R build i.e. 2.2.0. I have attached the code for data at the end of this mail so you can reproduce the problem. In short, I am able to run fitdistr under 2.1.0 without problems, while I get the following error under 2.2.0 (Version 2.2.0 Patched (2005-11-15 r36348)) > fitdistr(otm, "gamma") Error

Dear all, I am running a logistic regression and this is the output: glm(formula = educationUniv ~ brncntr, family = binomial) Deviance Residuals: Min 1Q Median 3Q Max # ???? ????? ?? ???????? -0.8825 -0.7684 -0.7684 1.5044 1.6516 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -1.06869 0.01155 -92.487 <2e-16 *** brncntrNo

On 10/25/2017 12:10 PM, Evgeny Astigeevich via llvm-dev wrote: > > Hi Chandler, > > I ran the LNT benchmarks and SPEC2k6.train on AArch64 Cortex-A57. I > used revisions: Clang 316561, LLVM 316563. > > Options: -O3 -mcpu=cortex-a57 -fomit-frame-pointer > -fexperimental-new-pass-manager > > Regressions: execution time increase > > LNT > >

On 10/25/2017 12:32 PM, Evgeny Astigeevich wrote: > > Hi Hal, > > I quickly checked the execution profile. It is real. The code changed > significantly. A number of the hottest regions changed. I’ll compare IRs. > Thanks. Obviously a 1000% execution performance regression seems problematic. -Hal > JFYI FreeBench/fourinarow time graph: >

Dear R helpers I have following dataset rate_number = matrix(c(5, 15, 60, 15, 5, 0, 20, 60, 20,0, 10, 20, 40, 20, 10), nrow = 5, ncol = 3) range_mat = matrix(c(6.25, 6.75, 7.25, 8.75, 9.25, 9.75, 8.5, 9, 9.5, 10.5, 11, 11.5, 4.25, 4.75, 5.25, 5.75, 6.25, 6.75), nrow = 6, ncol = 3) > rate_number        [,1]   [,2]   [,3] [1,]    5     0      10 [2,]   15   20      20 [3,]   60   60      40

I am sure there is something simple here I am missing, so please bear with me. It concerns the computation of the confidence interval for a population mean. The data are 125 measurements of Cs137 radation, a sample data set from Davis "Statistics and Data Analysis in Geology" 3rd ed. (CROATRAD.TXT) ------------------ method 1: using textbook definitions: mean \pm se_mean * t-value mu

Hi, I'm trying to use the R Survival analysis on a windows 7 system. The input data format is described at the end of this mail. 1/ I tried to perform a survival analysis including stratified variables using the following formula. cox.xtab_miR=coxph(Surv(time, status) ~ miR + strata(sex,nbligne, age), data=matrix) and obtain the following error message Warning message: In fitter(X, Y,

Hi, all. I want to write some functions like glm() so i studied it. In glm.fit(), it calls a fortran subroutine named "dqrfit" to compute least squares solutions to the system x * b = y To learn how "dqrfit" works, I just follow how glm() calls "dqrfit" by my own example, my codes are given below: > qr <- >

On Wed, May 29, 2013 at 03:25:30PM +0200, Duncan Sands wrote: > Hi Jack, I pulled the loop vectorizer and fast math changes into the 3.3 branch, > so hopefully they will be part of 3.3 rc3 (and 3.3 final!). It would be great > if you could redo the benchmarks rc3. > Duncan, As requested, appended are the updated Polyhedron 2005 benchmark results with both RC1 and RC3 llvm 3.3

Hello, I have the following loop for two data sets: diveData_2008 and diveData_2009. It uses two other data: diveCond_all and fishTable. The problem is at the point to identify the dive_id for the given index (index is timestamp). It keeps on saying for the1st loop Error in fishReport$dive_id[i] <- dive_id : replacement has length zero for the 2nd loop Error in fishReport$dive_id[i + j] <-

Hello, Two lapply questions (system info and sample data below): 1) Why does the first form of command1 add the name of y _after_ the str() output rather than before as does the second (preferred) form? # command1 version1 invisible(lapply(ls(pattern='bn'), function(y) cat(y, "\n", str(get(y)), "\n") )) # command1 version2 (preferred output)

Below are the results for the Polyhedron 2005 benchmarks compiled with llvm/compiler-rt/dragonegg 3.3svn at r182439 against current FSF gcc 4.7.3svn and 4.8.1svn. The only major bug remaining in the dragonegg 3.3svn support for gcc 4.8.x is http://llvm.org/bugs/show_bug.cgi?id=15980 which results in unresolved symbols for _iround and _iroundf in the aermod and rnflow testcases. Note that this