similar to: why does arima returns "NAN" standard error?

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

Hello everybody! I have an ARIMA model for a time series. This model was obtained through an auto.arima function. The resulting model is a ARIMA(2,1,4)(2,0,1)[12] with drift (my time series has monthly data). Then I perform a 12-step ahead forecast to the cited model... so far so good... but when I look the plot of my forecast I see that the result is really far from the behavior of my time

hallo to all I've to calculate an arima model and I need only the first and 365 th parameter and also the sar1 and the intercept, so I'm traing with: arima(X,order=c(365,0,0),seasonal=list(order=c(1,0,0),..),fixed=c(NA,rep(0,363),NA,NA,NA),transform.pars=F) but the error answer is: Error in polyroot(z) : polynomial degree too high (49 max) also there are problems in allocating memory

Rob J Hyndman gives great explanation here (https://robjhyndman.com/hyndsight/estimation/) for reasons why results from R's arima may differ from other softwares. @iacobus, to cite one, 'Major discrepancies between R and Stata for ARIMA' (https://stackoverflow.com/questions/22443395/major-discrepancies-between-r-and-stata-for-arima), assign the, sometimes, big diferences from R

Hi all, Using: R version 2.8.1 Patched (2009-03-07 r48068) on OSX (10.5.6) with survival version: Version: 2.35-3 Date: 2009-02-10 I get the following using the first example in ?summary.survfit: > summary( survfit( Surv(futime, fustat)~1, data=ovarian)) Call: survfit(formula = Surv(futime, fustat) ~ 1, data = ovarian) time n.risk n.event survival

Hi there, Everytime when I paste My R output in WORD, the columns couldn't line up nicely like they appear in R console. Is there a way to fix this problem? Thanks for any help! time n.risk n.event survival std.err lower 95% CI upper 95% CI 6 21 3 0.857 0.0764 0.707 1.000 7 17 1 0.807 0.0869 0.636 0.977 10 15 1

Hello R People: When using the arima function with the seasonal option, are the seasonal options only good for monthly and quarterly data, please? Also, I believe that weekly and daily data are not appropriate for seasonal parm estimation via arima. Is that correct, please? Thanks, Sincerely, Laura Holt mailto: lauraholt_983 at hotmail.com download!

Dear List, How do I extract the approximate Wald test for the frailty (in the following example 17.89 value)? What about the P-values, other Chisq, DF, se(coef) and se2? How can they be extracted? ######################################################> kfitm1 Call: coxph(formula = Surv(time, status) ~ age + sex + disease + frailty(id, dist = "gauss"), data = kidney)

Hi all, Does anyone have an example of an autoregressive (AR) time-series model specified as a state space model in R? That is, I want to go beyond the locally linear (constant) model, and fit the following Gaussian AR state process model: Xt = a + (1+b)*Xt-1 + epsilon ,where the model for the observation process is Yt = Xt + tau I have information of the tau's (observation variance)

Let's say I have a variable, day, which is saved as a factor with 7 levels, and I use it in a logistic regression model. I ran the model using the car package in R and printed out the results. mod1 = glm(factor(status1) ~ factor(day), data=mydat, family=binomial(link="logit")) print(summary(mod1)) The result I get is: Coefficients: Estimate Std. Error z value

I've been trying to get comfy with arima() and associated functions in the ts() package. I'm thinking seriously about using this package, and R generally, in a 4th year intro time series course that I'm teaching this autumn. I have a couple of questions about arima: (1) The help file says that residuals component of the value returned by arima() consists of the

Dear R-help list, I'd like to create visualize the clustering of a dataset with a dendrogram. I'm using the following script: data = read.table("data.csv", header=T, sep=";") require(cluster) res = as.dendrogram(agnes(data)) chlab <- function(n) { if(is.leaf(n)) { att <- attributes(n) labx <- data$category1[att$label] lab_color <- ifelse(labx ==

Hi, I've got a little problem using auto.arima. I run the following command auto.arima(drivers,ic="aic",d=1,D=1,max.order=10,max.p=5,max.q=5,max.P=5,max.Q=5,stepwise=FALSE,allowdrift=FALSE) and I get the following output : Series: drivers ARIMA(0,1,1)(5,1,1)[12] Coefficients: ma1 sar1 sar2 sar3 sar4 sar5 sma1 -0.6421

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

Dear R users, I am using plm packege in R to build my model, but from the result I can't quite figure out what it is... Can anyone tell me why? Am I missing something? R Results: *> ar1<-plm(formula=ADOP~lag(ADOP,1)+PE+WOR, + data=well, effect="time",model="within") > summary(ar1)* Oneway (time) effect Within Model Call: plm(formula = ADOP ~ lag(ADOP, 1) + PE

I'm using R to manipulate some data for testing nebulisers. I have a data frame as follows: Volt ABal 0.4208 A1 0.3982 AF 0.4353 B1 0.3954 BF 0.4355 C1 0.3975 CF 0.4345 I also have a calibration curve loaded Voltage NaF LogNaF 1 0.3588 20 1.30103 2 0.3990 100 2.00000 3 0.4391 500 2.69897 If I try to

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

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)),

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 <-

I'm creating a lattice barchart based off a pretty complicated data structure. The barchart comes out quite nice ( thanks to lattice ) but the problem is that the horizontal axis comes out all scrunched because the barchart doesn't know that the intervals of Var.1 are really "associated" with the conditioning variable Var.2. Therefore, all the intervals of Var.1 are put on