similar to: select different variables from a list of data frames

On 14 October 2013 19:31, Arnold Schwaighofer <aschwaighofer at apple.com>wrote: > Renato, can you post the c code for the function and the assembly that gcc > produces? > Attached. Your initial example could be well handled by vectorization of strided > loops (and the mentioning of VLD3(.8?)/VST3(.8?) lead me to assume that > this is what happened). But the LLVM-IR you

I currently have a data frame whose rows correspond to each student and whose columns are different variables for the student, as shown below: Lastname Firstname CATALOG_NBR Email StudentID EMPLID Start 1 alastname afirstname 1213 *@uark.edu 10295236 # 12/2/2008 2 anotherlastname anotherfirstname 1213 **@uark.edu ## 10295236 9/3/2008 Xattempts Q1

I have end of semester teaching evaluation data of the following form: > head(evaluations) Course Prefix Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 1 2330301 2 4 3 3 3 4 4 1 2 5 4 1 1 1 1 2 2330301 2 3 3 3 3 3 5 1 2 5 8 1 1 1 1 3 2330301 2 4 4 3 3 4 4 2 2 5 9 1 1 1 1 4 2330301 2 2 1 1 3 4 5 1 2 5 8

Hello R users! I have several data frames where some of the variables have many missing observations. For example, Q1 in one of my data frames has over 66% of its observations missing. I have tried imputation with mice but it does not work for all the data frames and I get the following message or a similar message to this: iter imp variable 1 1 Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11

Hello, I'm using the "sem" package to do a confirmatory factor analysis on data collected with a questionnaire. In the model, there is a unique factor G and 23 items. I would like to calculate the standardized residual variance of the observed variables. "Sem" only gives the residual variance with the "summary" function, or the standardized loadings with the

Hello: Forgive me, this is surely a simple question but I can't figure it out, having consulted the help archives and "Data Manipulation With R" (Spector). I have a list of 11 data frames with one common variable in each (prov). I'd like to use lapply to go through and recode one particular level of that common variable. I can get the recode to work, but it only returns the

On 21 September 2012 09:28, Sebastien DELDON-GNB <sebastien.deldon at st.com> wrote: > declare <16 x float> @llvm.arm.neon.vmaxs.v16f32(<16 x float>, <16 x float>) nounwind readnone > > llc fails with following message: > > SplitVectorResult #0: 0x2258350: v16f32 = llvm.arm.neon.vmaxs 0x2258250, 0x2258050, 0x2258150 [ORD=3] [ID=0] > > LLVM ERROR: Do not

I was up late last night, and i had a thought on peeling that would probably provide 100% accurate peeling data to a decoder, but take a maximum of 1101 times normal time to encode (taking into account the range from q-1 to q10 ). ay you want to encode a track at q10, but you want it to be peelable. the 1101 encoder would encode from the source at every quantifiable level (since there are 2

Renato, can you post the c code for the function and the assembly that gcc produces? Your initial example could be well handled by vectorization of strided loops (and the mentioning of VLD3(.8?)/VST3(.8?) lead me to assume that this is what happened). But the LLVM-IR you sent has a store of 0 in there ;) and strides by 4. Thanks, Arnold Vectorization of strided loops: I am using float as the

Hello Renato, You're pointing me at ARM intrinsics related to loads, problem that I've reported in original e-mail, is not support for vector loads, but support for 'vmaxs'. For instance, there is no vector loads of 16 floats in ARM ISA but it is legal to write in LLVM: ; ModuleID = 'vadd.ll' target datalayout =

Hi I was surprised with size of Theora files and thought of feedback. Following 1minute duration Theora and Xvid files were made from a y4m file. The resolution is 1280x720: 1. Xvid 17MB 2. Ogg/Theora Q7 31MB 3. Ogg/Theora Q8 38MB 4. Ogg/Theora Q9 49MB 5. Ogg/Theora Q10 61MB The Xvid file was made using mencoder by 2 passes with following options:

Hello everyone. I am new to R, so please bear with me. I am trying to find an easy way to export descriptive statistics and other information about my data frame to a LaTeX format. I have found the describe function in PrettyR to be very helpful in producing results in the exact format I'm looking for. However, the value of the describe function is a LIST (rather than a data frame) which I

--- silk/NSQ_del_dec.c | 37 +++++++++++++------------------------ silk/mips/NSQ_del_dec_mipsr1.h | 3 ++- 2 files changed, 15 insertions(+), 25 deletions(-) diff --git a/silk/NSQ_del_dec.c b/silk/NSQ_del_dec.c index aff560c..aaa1fca 100644 --- a/silk/NSQ_del_dec.c +++ b/silk/NSQ_del_dec.c @@ -31,6 +31,8 @@ POSSIBILITY OF SUCH DAMAGE. #include "main.h" #include

--- silk/NSQ_del_dec.c | 37 +++++++++++++------------------------ silk/mips/NSQ_del_dec_mipsr1.h | 3 ++- 2 files changed, 15 insertions(+), 25 deletions(-) diff --git a/silk/NSQ_del_dec.c b/silk/NSQ_del_dec.c index aff560c..aaa1fca 100644 --- a/silk/NSQ_del_dec.c +++ b/silk/NSQ_del_dec.c @@ -31,6 +31,8 @@ POSSIBILITY OF SUCH DAMAGE. #include "main.h" #include

This is almost ideal for SLP vectorization, except for two problems: 1. We have 4 stores to consecutive locations, but the last element is the constant zero, and not an additional SUB. At the moment we don’t have support for idempotence operations, but this is something that we should add. 2. The values that we are subtracting come from 3 loads. We usually load 4 elements from memory, or

I know this is something simple that I cannot do because I do not yet "think" in R. I have a data frame has a variable participation (a factor), and several other factors. I want a chisq test (no contingency tables) for participation vs all of the other factors. In SPSS I would do: CROSSTABS /TABLES= (my other factors) BY participation /FORMAT=NOTABLES /STATISTICS=CHISQ

This is my first post to R-help and I look forward receiving some advice for a novice like me... I?ve got a simple repeated (4 periods so far) 10-question survey data that is very easy to work on Excel. However, I?d like to move the compilation to R but I?m having some trouble operating on count list data in a neat way. The data C > str(C) 'data.frame': 551 obs. of 13

Created corresponding unit test, and the optimization is bit exact with C function. This optimization speeds up SILK encoder on NEON as following. Fixed-point: Complexity 0-5: 0% Complexity 6-7: 6% Complexity 8-9: 10% Complexity 10: 8% Got similar results on floating-point. --- silk/NSQ_del_dec.c | 6 +- silk/SigProc_FIX.h | 4

I took 5 albums (Classical music) and converted them to Ogg Vorbis at "Full Bitrate" (-q10) and all 5 directories take up about 775 Megs which won't fit on a CD. So I ripped them again in WAV first (And give my friend back his CDs) but now I wanna know what quality setting should I use to fit them on 1 CD (The highest possible with total space used just under 700 Megs)

R Experts, I have a dataframe made up of character vectors--these are results from survey questions. I need to convert them to factors. I tried the following which did not work: scs2<-sapply(scs2,as.factor) also this didn't work: scs2<-sapply(scs2,function(x) as.factor(x)) After doing either of above I end up with >str(scs2) chr [1:10, 1:10] "very important" "very