search for: ma1

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" "ma1" &qu...

Hi !            I am new to R. Can somebody help me in reformatting huge output files ,i.e, rearranging sets of columns in specific order. For example: I have data for three compunds 1, 2 and 3 file1: ID CA1 CA3 CA2 MA2 MA1 MA3 1 14 15 13 7 12 3 2 19 7 12 10 14 5 3 21 12 19 6 8 9   to File 2:   ID CA1 CA2 CA3 MA1 MA2 MA3 1 14 13 15 12 7 3 2 19 12 7 14 10 5 3 21 19 12 8 6 9   or File3: ID CA1 MA1 CA2 MA2 CA3 MA3 1 14 12 13 7 15 3 2 19 14 12 10 7 5 3 21 8 19 6 12 9   Thanks for your help, Tul Gan __...

Hi I am trying to define a function fu() in the following way but when I try to run I get the error that ma1 is not found. I am not sure where I am going wrong? Does the scope of ma1 not extend to an expr.frame object? expr.frame() is under library tradesys. function (y,ma1,ma2) { x <- y[, c("Open","Close")] d <- expr.frame(x, list(MAf=quote(SMA(Close, ma1)), MAs=quote(SMA(Clos...

...ie. I've tried to search, but my search skills don't seem up to finding what I need. (Maybe I don't know the correct terms?) I need the standard errors and not the confidence intervals from an ARIMA fit. I can get fits: > coef(test) ar1 ma1 intercept time(TempVector) - 1900 0.801459585 0.704126549 12.854527065 0.000520366 And confidence intervals: > confint(test) 2.5 % 97.5 % ar1 7.684230e-01 0.834496136 m...

...And the order is (1,1)*(0,1)45 The regular AR=1; regular MA=1; seasonal AR=0; seasonal MA=1; seasonal period=45. I fitted the model in R and get the result as below: Call:arima(x = cDownRange, order = c(1, 0, 1), seasonal = list(order = c(0, 1, 1), period = 45)) Coefficients: ar1 ma1 sma1 0.7364 -0.5046 -0.9511 s.e. 0.0458 0.0594 0.0130 When I use the predict command of this model in R, it gives the right forcasting. So I think the forcast formula of this SARMA model should be written as below: X(t)=ar1*X(t-1)-ma1*a(t-1)-sma1*a(t-45)+ma1*sma1*a(t-46) Bu...

...side" the function to figure out what "beets2" is? Best regards S?ren ________________ library(pbkrtest) data(beets) lgs <- lmer(sugpct~block+sow+harvest+(1|block:harvest), data=beets, REML=F) foo <- function(){ ## 1) beets2 <- transform(beets, yy = sugpct * yield) ma1 <- lmer(yy~block+sow+harvest+(1|block:harvest), data=beets2, REML=F) ma0 <- update(ma1, yy~.) ## 2) cl <- getCall(lgs) cl[["data"]] <- beets2 mb1 <- eval(cl) mb0 <- update(mb1, yy~.) mb0 ## 3) cl <- getCall(lgs) cl[["data"]] <- as.name(&qu...

...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 0.0646 s.e. 0.0865 0.0885 0.1141 0.1181 0.1196 0.1220 0.1120 0.0908 0.0865 ma1 ma2 sma1 -0.0221 -0.9779 -0.7635 s.e. 0.0539 0.0534 0.0834 sigma^2 estimated as 1.965e+17: log likelihood = -3316.07, aic = 6658.13 and in In R 2.11.1 Call: arima(x = xdata, order = c(p, d, q), seasonal = list(order = c(P, D, Q), period = S), optim.control = list(rel...

I can get an array of strings for the data that I want using 'paste()' as follows: paste('ma', 1:am$arma[2], '=', coef(am)[1:am$arma[2] + am$arma[1]], sep='') This results in a vector of strings like: [1] "ma1=1.17760133668255" "ma2=0.649795570407939" "ma3=0.329456750858276" What I would like is fixed.pars <- list(ma1=1.17760133668255,ma2=0.649795570407939,ma3=0.329456750858276) Is there an 'R' guru that would be willing to suggest a good way of doing this...

...ll repeat v_i[j] exactly i_1[j] times, like so: >rep(c(1,2,3),c(3,2,1)) [1] 1 1 1 2 2 3 > I'd like to do the same sort of thing where I replace v_1 with a matrix, and the jth row of the matrix is repeated i_1 times. Obviously, I could do this with for loops, like the following: >(ma1=matrix(1:6,nrow=2)) [,1] [,2] [,3] [1,] 1 3 5 [2,] 2 4 6 >vr1=c(2,3) >rma1=NULL >for(i in 1:length(vr1)){for(j in 1:vr1[i]){rma1=rbind(rma1,ma1[i,])}} >rma1 [,1] [,2] [,3] [1,] 1 3 5 [2,] 1 3 5 [3,] 2 4 6 [4,] 2 4 6 [5,]...

Hello. I am using fGarch to estimate the following model: Call: garchFit(formula = fmla, data = X[, i], trace = F) Mean and Variance Equation: data ~ arma(1, 1) + garch(1, 1) Conditional Distribution: norm Coefficient(s): mu ar1 ma1 omega alpha1 beta1 -0.94934 1.00000 -0.23211 54.06402 0.45709 0.61738 Std. Errors: based on Hessian Error Analysis: Estimate Std. Error t value Pr(>|t|) mu -0.949336 11.600072 -0.082 0.93477 ar1 1.000000 0.005947 168.139 < 2e-16 *** ma1 -0.23...

...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 X_t=(1+ma1*B+ma2*B^2+...)(1+sma1*B^s+sma2*B^2s+....) a_t For example: > m1=arima(koeps,order=c(0,1,1),seasonal=list(order=c(0,1,1),period=4)) > m1 Call: arima(x = koeps, order = c(0, 1, 1), seasonal = list(order = c(0, 1, 1), period = 4)) Coefficients: ma1 sma1 -0.4096 -0.8203 s.e....

...quot; "Region" "Total" "LocID" "UTMX" "UTMY" "Class" "cat3_name" "EventID" "day_sampl" "uniqueID" > > x3_reg1 <- x3[x3$Region == "JELA_reg1",]> > ma1 <- ftable(xtabs(Total ~ uniqueID + cat3_name, data=x3_reg1))> ma1 cat3_name Anthropogenic Asteraceae - herb Bare ground Canopy tree Coarse woody debris Cypress knees Emergent aquatic Epiphyte Floating aquatics Grasses Herbs Ilex Midstory tree Palm Sapium seb...

Dear All, I have a model to predict time series data for example: data(LakeHuron) Lake.fit <- arima(LakeHuron,order=c(1,0,1)) then the function predict() can be used for predicting future data with the model: LakeH.pred <- predict(Lake.fit,n.ahead=5) I can see the result LakeH.pred$pred and LakeH.pred$se but I did not see residual in predict function. If I have a model: [\ Z_t =

Full_Name: Ahmad Abu Hammour Version: rw0651 OS: windows 95 Submission from: (NULL) (63.23.128.44) Although I know that "ts package" is preliminary, I wanted to compare the results from R and SPSS. I ran ARIMA(2,1,2) in both softwares. I got NaN in standard errors of coefficients from R and real figures from SPSS. I changed "delta" in R to match that used by SPSS, I received

I did a regression with ARMA errors using arima0 with ari<-arima0(y,order=c(2,0,2),xreg=reg1,delta=-1) or ari<-arima0(y,order=c(2,0,2),xreg=reg1) where reg1 is the matrix of the regressors and when I see diag(ari$var.coef) I get negative terms. Do you know what this mean ? I try to change transform.pars to 0 or 1 but this crash R on Windows. Is it possible to test the significativity

...T2Ts[,4], order=c(2,1,2), > xreg=1:dlcpihTsLen) > **> dlcpiArma22hFit <- arima(ausT2Ts[,4], order=c(2,1,2)) > **> dlcpihArma22Fit > * > *Call: > **arima(x = ausT2Ts[, 4], order = c(2, 1, 2), xreg = 1:dlcpihTsLen) > * > *Coefficients: > ** ar1 ar2 ma1 ma2 1:dlcpihTsLen > ** -0.1083 0.8673 0.5263 -0.3716 0.0146 > **s.e. 0.0493 0.0484 0.0894 0.0852 0.0041 > * > *sigma^2 estimated as 0.0001282: log likelihood = 498.38, aic = -984.76* * * * * I wonder why the coefficient values are little bit diff...

Dear R People: I'm trying to use the predict command on an arima0 object. I do the following: xm.arma <- arima0(xm2,order=c(1,0,1)) predict(xm.arma,n.ahead=2) and I get the message: Error in round(x, digits) : Non-numeric argument to mathematical function Any ideas what the problem might be, please? R version 1 4 1 on Windows. Thanks in advance! Sincerely, Erin Hodgess Associate

...nd the fit of diff(x) with an arma (same coeff p & d) differ one from another here are the output of R: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% > modelarma<-arma(diff(x),c(7,5)) > modelarma Call: arma(x = diff(x), order = c(7, 5)) Coefficient(s): ar1 ar2 ar3 ar4 ar5 ar6 ar7 ma1 ma2 0.06078 -0.44774 0.41881 0.47624 0.01406 0.06565 -0.06167 -0.01294 0.31313 ma3 ma4 ma5 intercept -0.49027 -0.55461 -0.11520 -0.10692 > modelarima<-arima(x,c(7,1,5)) > modelarima Call: arima(x = x, order = c(7, 1, 5)) Coefficients: ar1 ar2 ar3 ar4 ar5 ar6 ar7 ma1 ma2 ma3 ma4 0.1244...

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.coe...

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 know how to solve this problem??? That would be great! Thanks a lot for your help!! Best regards, Katharina [[alternative HTML version deleted]]