similar to: Lattice xyplot and groups

# Dear R Community, # I have this data frame: df1 <- data.frame( F1 = factor( c( rep("D1",12),rep("D2",12),rep("D3",12) ) ), F2 = factor( rep( rep( paste("O",1:6,sep=""), rep(2,6) ), 3) ), F3 = factor( rep( c("V1","V2"), 18 ) ), S1 =

Dr. Williams, I ran across your inquiry on one of the R-help mailing lists regarding digital filter design and implementation. I found no response to your email in the archives and was wondering if you were able to find anything. Thanks, Israel -- Israel Christie, Ph.D. Email: ichristie at gmail.com Phone: 865.766.0214 Mobile: 865.406.4615

I'm doing convolutions in the frequency domain and need to know the layout of the Fourier modes returned by fft. (This is leading up to a more involved question about moment generating functions, but I need to know if I've got this part correct first.) I think in 1D the pattern is: 0 1 2 3 -2 1 (even) 0 1 2 3 -3 2 1 (odd) In 2D is it simply (for a square matrix): 0 1 2 -1 (horizontal)

Dear mailing list, I have following array: X2 Y2 [1,] 422.7900 6.0 [2,] 469.8007 10.5 [3,] 483.9428 11.0 [4,] 532.4917 25.5 [5,] 596.1942 33.5 [6,] 630.8496 40.5 [7,] 733.2996 45.0 [8,] 946.4779 32.0 [9,] 996.8068 35.5 [10,] 1074.3310 23.0 I do afterwards the following: plot.new() plot.window(xlim=c(min(X1)-50,max(X1)+50),

To reduce memory consumption clobbered registers are handled with RegisterMask machine operands which contain a bitset of all registers clobbered. - Matthias > On Jul 29, 2015, at 3:00 PM, Daniel Sanders <daniel.sanders at imgtec.com> wrote: > > I believe I've identified the problem with almabench but I haven't found the root cause in the compiler yet. > > The

Dear all, I am having trouble creating summary tables using aggregate function. given the following table: Var1 Var2 Var3 dummy S1 T1 I 1 S1 T1 I 1 S1 T1 D 1 S1 T1 D 1 S1 T2 I 1 S1 T2 I 1 S1 T2 D 1 S1 T2 D 1 S2

Hi, I'm trying to get maximum likelihood estimates of \alpha, \beta_0 and \beta_1, this can be achieved by solving the following three equations: n / \alpha + \sum\limits_{i=1}^{n} ln(\psihat(i)) - \sum\limits_{i=1}^{n} ( ln(x_i + \psihat(i)) ) = 0 \alpha \sum\limits_{i=1}^{n} 1/(psihat(i)) - (\alpha+1) \sum\limits_{i=1}^{n} ( 1 / (x_i + \psihat(i)) ) = 0 \alpha \sum\limits_{i=1}^{n} (

On Tue, 12 Oct 2004 14:01:21 -0500 (CDT) Chris Lattner <sabre at nondot.org> wrote: > On Tue, 12 Oct 2004, Morten Ofstad wrote: > > > This is my first post on this mailing list, so bear with me... My name > > is Morten Ofstad and I work for Hue AS (www.hue.no), a company that > > makes 3D Visualization software. We are looking into using LLVM for JIT > >

Hello there, I wish to solve the following nonlinear System of equations: + u1 - Vmax11*S1/(S1 + Km11 *(1 + S2/Km21)) - Vmax12*S1/( S1 + Km12 *(1+S2/Km22)) == 0 + u2 - Vmax22*S2/(S2 + Km22 *(1 + S1/Km12)) - Vmax21*S2/( S2 + Km21 *(1+S1/Km11)) == 0 + Vmax11*S1/(S1 + Km11 *(1 + S2/Km21)) + Vmax12*S1/( S1 + Km12 *(1+S2/Km22)) - d1*P1 == 0 + Vmax22*S2/(S2 + Km22 *(1 + S1/Km12)) + Vmax21*S2/( S2 +

I have three modules: ----------------------------------------------------------------- s1.ll: %0 = type <{ i32, i32 }> define void @s1(%0* byval %myStruct) nounwind { return: ret void } ----------------------------------------------------------------- s2.ll: %0 = type <{ i32, i32 }> define void @s2(%0* byval %myStruct) nounwind { return: ret void }

Hello, I have a problem with rsync and hard links : I have 1 folder : P, with 2 subfolders : S1 and S2 S2 contains a lot of hard links to file stored in folder S1. P : -S1 -S2 (S2 files hard links to S1 files) I would like to rsync the folder P to another computer, but each sub folder S1 (110 Go) and S2 (10 Go + hard link to 100 Go of S1) contains thousands of thousands of

Hello everyone, I am stuck with an apparently simple issue : i) I have two sets S1 and S2, each containing a large number of integers, say zip codes. ii) Now, I just want to test whether a particular zip code belong to S1 or S2 or neither of them. iii) If it belongs to S1, the area/region gets a particular label, say 1; if it belongs to S2, it gets a label 2 and if it doesnot belong to either S1

Hi Jean-Marc, Thanks a lot for reviewing this huge assembly function! silk_warped_autocorrelation_FIX_c()'s kernel part is for( n = 0; n < length; n++ ) { tmp1_QS = silk_LSHIFT32( (opus_int32)input[ n ], QS ); /* Loop over allpass sections */ for( i = 0; i < order; i++ ) { /* Output of allpass section */ tmp2_QS = silk_SMLAWB(

Hello, This is my first post on this mailing list, so bear with me... My name is Morten Ofstad and I work for Hue AS (www.hue.no), a company that makes 3D Visualization software. We are looking into using LLVM for JIT compiling shader programs, to replace our own (slow) VM. A requirement for this is that we can compile LLVM in VS7.1, so I contacted Paolo Invernizzi to find the status of his

Hi James, So does this mean if the instruction could set the overflow flag, the instruction should not have [(set ... )] in it's pattern, i see this is the difference in instruction description for the mips case. I'm wondering how llvm knows when to use certain compare instructions such as SETNE or SETUNE? And for sign or zero extending loads? I can see the PatFrags described and the

Hey! Could you please take a quick look at what I have done? Somehow I get wrong results using the anova(lm()) combination compared to doing a two way ANOVA by hand. Running: Data<-read.table("Data.txt"); g<-lm(ExM~S1*S2,Data); anova(g); Gives: Analysis of Variance Table Response: ExM Df Sum Sq Mean Sq F value Pr(>F) S1 1 4.3679

I am trying to create my own Token Bucket Filter. However, I have a problem with packet dropping. Scenario : I got two streams 20KB/s each. I got one bucket with rate 20KB/s I put both streams into this bucket. When buffer is full packets need to be dropped. The problem is that only every other packet needs to be dropped in this scenario. Streams are the same so queue looks like that : S1 |

Hi everybody, consider please an optimization problem: minimize sum S1+S2 Subject to : y - x =< A + S1 x - y =< A + S2 and we want to add two more constraints: y - x =< B - S3 x - y =< B - S4 where A is a small constant value and B is a large constant value, S1 and S2 are surplus and S3

Hello R community, I am computing weighted average statistic by using ddply function: My data set is: N1 T1 S1 I1 C1 FY-4 ROE11 EPS11 MKT11 N1 T1 S1 I1 C1 FY-3 ROE12 EPS12 MKT12 N1 T1 S1 I1 C1 FY-2 ROE13 EPS13 MKT13 N1 T1 S1 I1 C1 FY-1 ROE14 EPS14 MKT14 N1 T1 S1 I1 C1 FY0 ROE15 EPS15 MKT15 N1 T1 S1 I1 C1 FY1 ROE16 EPS16 MKT16 N1 T1 S1 I1 C1 FY2 ROE17

This is a great idea. But the order (psEncC->shapingLPCOrder) can be configured to 12, 14, 16, 20 and 24 according to complexity parameter. It's hard to get a universal function to handle all these orders efficiently. Any suggestions? Thanks, Linfeng On Mon, Feb 6, 2017 at 12:40 PM, Jean-Marc Valin <jmvalin at jmvalin.ca> wrote: > Hi Linfeng, > > On 06/02/17 02:51 PM,