similar to: how to join two arrays using their column names intersection

Estimated people, I have two matrices: ar1 <- array(data=c(1:16),dim=c(4,4)) ar2 <- array(data=c(1,2,3,3,5:16),dim=c(4,4)) They only differ in the fourth row. I would like to compare them in order to know which columns are equal. The following works, but I would like to have a better solution, and not to use what someone called "prehistorical loops": for(i in

Dear members of the list, it is likely a stupid question but I cannot find the information neither in R manuals nor in google. I am generating a plot (from hclust results) but I cannot see properly the labels because the default font size is too large. How can I change it? Thanks! Federico

Hi, A quick question: I have to vectors, say ar1 and ar2 > ar1 [1] "a" "c" "c" "a" attr(,"levels") [1] "a" "b" "c" > ar2 [1] TRUE TRUE FALSE TRUE > table(ar1, ar2) ar2 ar1 FALSE TRUE a 0 2 c 1 1 I would like to obtain: T F a 2 0 b 0 0 c 1 1

Dear List, Below is a simple, standard loss model that takes into account the terms of an insurance policy: deductible <- 15 coverage.limit <- 75 insurance.threshold <- deductible + coverage.limit tmpf <- function() { loss <- rlnorm(rpois(1, 3), 2, 5) sum(ifelse(loss > insurance.threshold, loss - coverage.limit, pmin(loss, deductible))) } net <- replicate(1000000, tmpf())

Dear R People: I have the output from an arima model fit in an object xxx. I want to verify that the ma1 coefficient is there, so I did the following: > xxx$coef ar1 ar2 ma1 intercept 1.3841297 -0.4985667 -0.9999996 -0.1091657 > str(xxx$coef) Named num [1:4] 1.384 -0.499 -1 -0.109 - attr(*, "names")= chr [1:4] "ar1" "ar2"

Hello , I have estimated the following model, a sarima: p=9 d=1 q=2 P=0 D=1 Q=1 S=12 In R 2.12.2 Call: arima(x = xdata, order = c(p, d, q), seasonal = list(order = c(P, D, Q), period = S), optim.control = list(reltol = tol)) Coefficients: ar1 ar2 ar3 ar4 ar5 ar6 ar7 ar8 ar9 0.3152 0.8762 -0.4413 0.0152 0.1500 0.0001 -0.0413 -0.1811

I'm using the fixed argument in arima. Shouldn't ar4, ar5, and ar6 display as zero in the output? Call: arima(x = window(log(hhprice), start = c(1990, 1), end = c(2003, 3)), order = c(7, 1, 0), xreg = window(ts.union(exa1 = lag(exa, -1), exa12 = lag(exa, -12), exb1 = lag(exb, -1), exc1 = lag(exc, -1), exc12 = lag(exc, -12)), start = c(1990, 1), end = c(2003, 3)),

Dear users, I tried to fit an AR(2) model to data. This the result: > arima(vw,c(3,0,0)) Call: arima(x = vw, order = c(3, 0, 0)) Coefficients: ar1 ar2 ar3 intercept 0.1052 -0.0102 -0.1203 0.0099 s.e. 0.0337 0.0339 0.0338 0.0018 sigma^2 estimated as 0.002934: log likelihood = 1293.16, aic = -2576.33 Now, ar2 is not significantly different from

Evening, I was writing some code that tried to insert calls to the llvm.annotation intrinsic function, which has a signature of (i32, i8*, i8*, i32). The code is below. void addAnnotation( BasicBlock *block, Function *F) { string foo = "foo"; string bar = "barr"; Type *charTy = Type::getInt8Ty(block->getContext()); ArrayType *s1Ty =

Hello I want to fit an AR model were two of the coefficients are fixed to zero (the second and third ar-coefficients). I used the "arima" function with the "fixed" argument but the ar3 coefficient is not set to zero: ============================================== > arima(Y, order=c(4,0,0), xreg=1:23, fixed=c(NA,0,0,NA,NA,NA)) Call: arima(x = Y, order = c(4, 0, 0), xreg =

Dear all, The standard call to ARIMA in the base package such as arima(y,c(5,0,0),include.mean=FALSE) gives a full 5th order lag polynomial model with for example coeffs Coefficients: ar1 ar2 ar3 ar4 ar5 0.4715 0.067 -0.1772 0.0256 -0.2550 s.e. 0.1421 0.158 0.1569 0.1602 0.1469 Is it possible (I doubt it but am

Hi, This is likely an stupid question, but I cannot find the solution. I am searching for an "exit" function, to end the execution of an R script if some condition is not filled. Any clue? Thank you in advance! Federico

Andrew Ruef wrote: > Evening, > > I was writing some code that tried to insert calls to the > llvm.annotation intrinsic function, which has a signature of (i32, > i8*, i8*, i32). The code is below. > > void addAnnotation( BasicBlock *block, Function *F) > { > string foo = "foo"; > string bar = "barr"; > > Type

Hello, it might be a very simple question but I cannot find the solution (I tried a || b, any(a,b)... but none works). My problem is: I have two vectors, a <- c(TRUE,FALSE,FALSE) b <- c(TRUE,FALSE,TRUE) and I would like to obtain a vector that indicates if it is TRUE in any of the two vectors. Hence, the desired output would be: TRUE, FALSE, TRUE Thank you in advance, Federico

Hi, I am investigating a problem for which I found no solution. I have a matrix with two columns. I have plotted it as an x-y plot (plot(matrix[,1],matrix[,2]) But this is not apropriate for my purposes. I need to group the data in matrix[,1] into groups (as an histogram would do). Then I have to calculate the average of matrix[,2] for each group. Before starting with loops and loops I

hey can anybody help me? i have to simulate the richardson Arms race model on R.. for my simulation class...

When I do ARMA(2,2) using one lag of LCPIH data This is eview result > > *Dependent Variable: DLCPIH > **Method: Least Squares > **Date: 08/12/11 Time: 12:44 > **Sample (adjusted): 1970Q2 2010Q2 > **Included observations: 161 after adjustments > **Convergence achieved after 14 iterations > **MA Backcast: 1969Q4 1970Q1 > ** > **Variable Coefficient Std.

Hi, I want to model different timeseries with ARMAX models in R because I think that ARMAX models will map best to these data. Besides I don't want to use the order of the AR or MA part but the lag e.g. AR Part =ar1, ar2, ar7; MA Part =ma1, ma3 and I want to use exogenous variables as well. I coudn't find any solutions in the R help and therefore I want to ask all of you. Does anyone

Hi everyone, ----------------------------- Coefficients: ar1 ar2 ma1 ma2 sar1 intercept drift 1.5283 -0.7189 -1.9971 0.9999 0.3982 0.0288 -9e-04 s.e. 0.0869 0.0835 0.0627 0.0627 0.1305 NaN NaN sigma^2 estimated as 0.04383: log likelihood = 4.34, aic = 7.32 Warning message: NaNs produced in: sqrt(diag(object$var.coef))

I'm trying to use the following command. arima (x, order = c(p,d,q), seasonal =list(order=c(P,D,Q), period=s) How can I write an estimated seasonal ARIMA model from the outputs. To be specifically, which sign to use? I know R uses a different signs from S plus. Is it correct that the model is: (1-ar1*B-ar2*B^2-...)(1-sar1*B^s-sar2*B^2s-....)(1-B)^d(1-B^s)^D