search for: y9

....06,0.83,1.00,0.41,0.93,1.01,0.86) y2=c(0.05,0.16,0,0.26,0.15,0.61,0.33,0.31,0.33) y3=c(-0.23,0,0.16,-0.03,0.22,-0.03,-0.17,-0.05) y4=c(0.04,-0.21,-0.04,-0.26,-0.03,-0.04,-0.05) y5=c(-0.02,-0.34,0.06,-0.22,-0.11,-0.31) y6=c(0.20,0.01,0.01,-0.26,0.01) y7=c(-0.06,-0.14,0.39,0.23) y8=c(0.21,0.10,0.09) y9=c(-0.24,-0.23) y10=c(0.13) y=c(y1,y2,y3,y4,y5,y6,y7,y8,y9,y10) ## autoregressive paramters ,table 1 biometrika 1999,page 685 om2=matrix(0,nrow=55,ncol=3) om1=poly(c(1:10),degree=3) ##polynomial design matirx with level =11,cubic om2[1:10,]=t(matrix(rep(om1[1,],10),ncol=10)) om2[11:19...

...oad i32* %x %y4 = load i32* %y %add = add i32 %x3, %y4 %c5 = load i32* %c %add6 = add i32 %c5, %add store i32 %add6, i32* %c %y7 = load i32* %y %add8 = add i32 %y7, 1 store i32 %add8, i32* %y br label %Until2 Until2: ; preds = %Repeat2 %y9 = load i32* %y %b10 = load i32* %b2 %cond = icmp sge i32 %y9, %b10 br i1 %cond, label %Repeat2, label %Untilcmp2 Untilcmp2: ; preds = %Until2 %x11 = load i32* %x %add12 = add i32 %x11, 1 store i32 %add12, i32* %x br label %Until1 Until1:...

...= load i32* %x > %y4 = load i32* %y > %add = add i32 %x3, %y4 > %c5 = load i32* %c > %add6 = add i32 %c5, %add > store i32 %add6, i32* %c > %y7 = load i32* %y > %add8 = add i32 %y7, 1 > store i32 %add8, i32* %y > br label %Until2 > > Until2: ; preds = %Repeat2 > %y9 = load i32* %y > %b10 = load i32* %b2 > %cond = icmp sge i32 %y9, %b10 > br i1 %cond, label %Repeat2, label %Untilcmp2 > > Untilcmp2: ; preds = %Until2 > %x11 = load i32* %x > %add12 = add i32 %x11, 1 > store i32 %add12, i32* %x > br label %Until1 > > Until1: ; pred...

...t;A4" "A5" "A6" "A7" "A8" "A9" "A10" Now assign each element as name for a data frame: (d <- data.frame(cbind(X1=1,Y1=1:10,X2=1,Y2=1:10,X3=1,Y3=1:10,X4=1,Y4=1:10,X5=1,Y5 =1:10, X6=1,Y6=1:10,X7=1,Y7=1:10,X8=1,Y8=1:10,X9=1,Y9=1:10,X10=1,Y10=1:10))) x <- paste("X",1,sep="") y <- paste("Y",1,sep="") for (i in 2:10) {x[i] <- paste("X",i,sep="") y[i] <- paste("Y",i,sep="")} for (k in 1:10) {assign(char[k],d[,c(x...

...) { I = which(D[,k]==-999) if (length(I) > 0) { D[I,k] = NA } } The dataset has many missing values. I am running several regressions on this dataset, and want to ensure every regression has the same subjects. Thus I want to drop subjects listwise for dependent variables y1-y9 and covariates x1-x5 (if data is missing on ANY of these variables, drop subject). How would I do this after running the syntax above? Thank you [[alternative HTML version deleted]]

...hought about comparing confidence intervals, but if I understand correctly the confidence intervals are calculated from the unstandardized beta weights, which in this case would not help me, correct? (2) The strength of the same predictor over different models. I want to say whether x1 affects y1 - y9 equally strong or not. How would I do this? I hope that I provided all information that is needed. Thank you T [[alternative HTML version deleted]]

...19 X110 X111 X112 X113 X114 1 2 1 2 1 2 1 2 1 2 1 2 1 2 X115 X116 X21 X22 X23 X24 X25 X26 X27 X28 X29 X210 X211 X212 1 2 0 1 0 1 1 1 0 1 0 1 0 1 X213 X214 X215 X216 Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10 1 1 0 1 1 2 3 4 5 6 7 8 1 2 Y11 Y12 Y13 Y14 Y15 Y16 3 4 5 6 7 8 So, e.g. for a 3 column matrix: > matrix(do.call(c,imp), ncol=3) [,1] [,2] [,3] [1,] 1 0 1 [2,] 2 1 2 [3,] 1 0 3 [4,] 2...

Hello everyone, I want to transform a data.frame into an array (lets call it mydata), where: mydata[[1]] is the first imputed dataset...and for each mydata[[d]], the first p columns are covariates X, and the last one is the outcome Y. Lets assume a simple data.frame: Imputed = data.frame( X1 = c(1,2,1,2,1,2,1,2, 1,2,1,2,1,2,1,2), X2 =

...rpose the method ?confint? will return a wrong evaluation of the confidence interval without throwing any warning. I suggest to use the fixed values that are already contained within the mle object: > fit0 at fullcoef[grep('y', names(fit0 at fullcoef))] y1 y2 y3 y4 y5 y6 y7 y8 y9 y10 y11 26 17 13 12 20 5 9 8 5 4 8 Additionally, the method ?coef? returns both the coefficient and the fixed parameters - while should return only the parameters - , while the ?fullcoef? method is not implemented - while present in the documentation of 'mle-class?. Best, S...

...19 X110 X111 X112 X113 X114 1 2 1 2 1 2 1 2 1 2 1 2 1 2 X115 X116 X21 X22 X23 X24 X25 X26 X27 X28 X29 X210 X211 X212 1 2 0 1 0 1 1 1 0 1 0 1 0 1 X213 X214 X215 X216 Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10 1 1 0 1 1 2 3 4 5 6 7 8 1 2 Y11 Y12 Y13 Y14 Y15 Y16 3 4 5 6 7 8 So, e.g. for a 3 column matrix: > matrix(do.call(c,imp), ncol=3) [,1] [,2] [,3] [1,] 1 0 1 [2,] 2 1 2 [3,] 1 0 3 [4,] 2...

...hich stands for gene expression divergence and 14 matrices which stands for gene sequence divergence. I have tried joining them by using the concatanation function giving SequenceDivergence <- c(X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14) ExpressionDivergence <- c(Y1,Y2,Y3,Y4,Y5,Y6,Y7,Y8,Y9,Y10,Y11,Y12,Y13,Y14) where X1,X2..X14 are the expression matrices containing r-values and Y1,Y2..Y14 are the ones with patristic distances Now, I want to plot SequenceDivergence vs. Expression Divergence Tried doing that using plot (Sequence Divergence vs. Expression Divergence) But then gett...

Dear all, im looking for a solution to protect an Exchange 2003 email server from direct "pop3-internet-connects". Is it possible that Dovecot act as a POP3-/POP3SSL-Proxy, "LDAP-authenticate" all user logins to a Windows 2003 domain controller and forward then all POP3-connects to a single Exchange 2003 server? Could someone give me some advices or a link for howtos for

...hich stands for gene expression divergence and 14 matrices which stands for gene sequence divergence. I have tried joining them by using the concatanation function giving SequenceDivergence <- c(X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14) ExpressionDivergence <- c(Y1,Y2,Y3,Y4,Y5,Y6,Y7,Y8,Y9,Y10,Y11,Y12,Y13,Y14) where X1,X2..X14 are the expression matrices containing r-values and Y1,Y2..Y14 are the ones with patristic distances Now, I want to plot SequenceDivergence vs. Expression Divergence Tried doing that using plot (Sequence Divergence vs. Expression Divergence) But then gett...

...5?9.0?32.5?0.01 Y3?4.5?14.5?14.2?9.2?0.6?14.5?1?7.5?22.9?0.05 Y4?5.9?16.2?24.6?12.7?0.2?24.3?3?8.0?26.8?0.04 Y5?7.2?20.4?40.6?18.2?0.8?28.2?5?9.2?44.3?0.02 Y6?5.9?18.6?37.4?14.5?0.3?36.9?8?9.5?32.9?0.10 Y7?8.0?16.1?88.6?24.1?0.1?34.6?2?8.7?11.1?0.02 Y8?13.6?21.1?56.3?19.0?0.7?33.3?6?9..5?10.8?0.06? Y9?11.2?20.4?40.7?12.9?1.1?40.3?3?12.2?6.5?0.04 Y10?7.6?18.3?27.5?8.1?2.3?41.9?2?5.9?2.9?1.00 Y11?8.8?22.2?33.3?8.8?0.6?44.4?4?6.6?55.5?0.09 Y12?9.4?16.5?35.6?16.2?0.7?50.2?5?8..8?31.4?0.07 ? (These files have been given as attachments as well) The data file has 10 variables in all, divided into?two...

Can somebody help me with the following issue (SEM in R), please:   When I run the model (includes second order models) in R, it gives me the following:   1)       In sem.default(ram = ram, S = S, N = N, param.names = pars, var.names = vars,  :   Could not compute QR decomposition of Hessian. Optimization probably did not converge.   2)       I have aliased parameters and NaNS   or sometimes when

DeaR useRs: I would like to assign a values in an object using a loop 'for'. This is a reduce example of my problem, my real problem is a few complicated: for (j in 1:10) { x.j<-rnorm(100) } I want to create 10 objects as "x.1, x.2, ... , x.9, x.10" with values in it. I used the "assign" function but nothing happens. Thank you very much

Hi All, I am making a serious effort to try to learn R, but one hurdle I am facing is that I need to "see" the data as I walk through the examples in the packages. For instance, many examples on the web start by a command like data("wines"). How can I actually view what the dataset looks like prior to transformations and analysis? I have tried to use edit() , print, and

..."y3",540,40,23,0,15,23,25,0,35,2,8 > "y4",610,45,25,0,16,26,28,0,40,2,8 > "y5",100,10,15,25,5,1,8,30,25,15,6 > "y6",150,3,3,0,11,9,6,0,0,20,10 > "y7",340,12,8,6,26,19,0,0,0,20,25 > "y8",300,5,3,0,16,20,11,0,0,10,8 > "y9",380,8,11,5,10,25,9,2,40,30,10 > "y10",40,5,0,0,2,1,2,0,0,0,0 > "y11",230,12,9,0,11,13,4,0,0,0,10 > "y12",180,0,0,0,0,14,0,6,210,4,2 > > --------------060007010402070602040701-- > > > --__--__-- > > Message: 4 > Date: Sat, 7 Dec 20...

...3*-H)?2[K@'5E$I[DJ9ED,%04XZ2^"RZ:Z:^:.3).ETHE98K[6E: MHXKIN%BXUC=07]/N9%WGHG4[9EJGGT!!H:J<5TUH/<C$],V^4HROL0!6]F-B MH6F.-40V,>NU9.P^*,'1[^6\)QA=6-^RUV]8W;(4!9*MS!397-])YX)-9:.% MG<?A7@<WW7:[V[:H[WAY17LNN65J@M*P4Y[0KM2ZN<R>C168M!>>I'MAJ[33 M744R<S[P24BG$Y9^5`$J5I!IKVBI#:"!/5>&T[\:]U[UAHCF@@")VFYZ9^K% M$1^,U>C0W[E\)1%!9$R1L;JV,M:A=5@TEL9OX7R>0%(/<$\!9=?R+IW/9_G[ M&BE4-L2XM#RUU3V#ES7H"R^(8+T3$3DN$%QZP36^CO!5-YU&(K1C`OW,8`WZ M7#L%T(\$UJ`[^B:_L.4OKM/9Q:FRTJWG8EQ:\FF"CX9RREV[_10,;.[NVH?6 M[IYJA_^)79C*!!]#?[G@$]^...

...j!U@Sg7f)1+!un& ze$nwY-nA1tYoM5QF>Q@U*Vkw%*{|U~5IpW2O@rip*dzNx^m#vq_bq~d_<RZp{K)&X ztrfWfK4hBVd!<?6A7NbHC&5#UXACtp^zUVSGJ?}t66NrIfxev6jhJiTa!#MO1;CHn zJhz>MY8}MjXR#UL#+k)th>P2_g>PE^E?IcP!aooH(Q(rLdjVBk+-|h}$nT=|_5<k0 z#sBRN^ZF<BW7g3*20U)QI5@|}$2kH0nDufVbwYi6y`0CPFY9Hki!<5QcdhU^OOIGw zyXmakS{A;I!N>Xk1~yO3es;dq!OyGkBkOX(^8Y;xx5xi_2R}dUfd2vG`S5!>wo$K* z;X-C?ZFP05e)fsX=IL4?zwQU8OU25@=9vC<8(XafIb7mYE~cxvta*B7*;`z=xPtql z_Vth#l)Y8DAgV(nU-i~X)tq1Q@<Fv$_xz1bwOTD-Efs=7K0WctPi5kj^u?3s*J}P2 z?ty~ZmU_14mkVBgqg>vCiN)!gsza*(@l<fbWF~TMdFuSEH@ox{-F)e3NjqP...