similar to: Overriding contributed package functions

I am using the ts package to fit ARIMA models, and the tsdiag() function to plot diagnostics. In doing so I'm generating an awful lot of diagnostic plots of different models and different data sets all within the same R session. So my question is, is there an option in tsdiag() similar to <main="Title"> that I can use? This would be quite helpful when I print out the plots,

Dear list, I am trying to re-analyse something. I do have two time series, one of which (ts.mar) might help explaining the other (ts.anr). In the original analysis, no-one seems to have cared about the data being time-series and they just did OLS. This yielded a strong positive correlation. I want to know if this correlation is still as strong when the autocorrelations are taken into account.

Hello, I'm getting the following error message when I try to run 'tsdiag' on what seems to be a valid time series: > tsdiag(small) returns: [Error in tsdiag(small) : no applicable method for "tsdiag"] where small is a little test series where I have isolated this problem (the original has 30-years worth of daily data) When I print it (small), it looks like the

Hi R Users, I'm fairly new to R (about 3 months use thus far.) I wanting to use the arimax function from the TSA library to incorporate some exogenous inputs into the basic underllying arima model.Then with that newly model of type arimax, I would like to make a prediction. To avoid being bogged down with issues specific to my own work, I would like to refer to readers to the example

Hi, I am newbie user of ggplot and would like some assistance in implementing time series plots. I'd like to know how the tsdiag plot can be made in ggplot? Thanks Harsh Singhal Decisions Systems, Mu Sigma Inc.

Hi R experts, I am trying to remove autocorrelation from Simple Moving Average time series. I know that this can be done by using seasonal ARIMA like, library(TTR) data <- rnorm(252) n=21 sma_data=SMA(data,n) sma_data=sma_data[-1:-n] acf(sma_data,length(sma_data))

Hi, I'm trying to model an ARMA(1,[1,4]), i.e. I want only lags 1 and 4 of the Moving Average part. It's the '[1,4]' part that is giving me a problem. I've tried different arma's and arima's in different packages, namely: packages tseries, fArma, FinTS, timeSeries, TSA, Zelig, ds1, forecast For example, with package FinTS: > ( ARIMA(y, order=c(1,0,c(1,4))) )

Dear R-helpers, I have a time series analysis problem in R: I want to analyse the output of my simulation model which is proportional cover of shrubs in a savanna plot for each of 500 successive years. I have run the model (which includes stochasticity, especially in the initial conditions) 17 times generating 17 time series of shrub cover. I am interested in a possible periodicity of shrub

i am using sarima() function as below ___________________________________________________________________________________________ sarima=function(data,p,d,q,P=0,D=0,Q=0,S=-1,tol=.001){ n=length(data) constant=1:n xmean=matrix(1,n,1) if (d>0 & D>0) fitit=arima(data, order=c(p,d,q), seasonal=list(order=c(P,D,Q), period=S),

Hi I'm trying to measure the effect of a policy intervention (Box and Tiao, 1975). This query has to do with the coding of the model rather than with the particulars of my dataset, so I'm not providing the actual dataset (or a simulated one) in this case, apart from some general description. The time series are of length n=34 (annual observations between 1977 and 2010). The policy

Hi, I am doing predictive modelling of Multivariate Time series Data of a Motor in R using various models such as Arima, H2O.Randomforest, glmnet, lm and few other models. I created a function to select a model of our choice and do prediction. Model1 <- function(){ .. return() } Model2 <- function(){ ... return() } Model3 <- function(){ ... return() } main <-

Hi, I want to give a summary or anova for "arima" model in R, as "summary", and "anova" for "lm". As including various intervention factors in arima(xreg = ) part, I want to assess the significancy of thse factors. I can do it using interrupted analysis of time series by linear regression, but want to see whether arima model works for the data first.

Hi, I would like to make a replication of 10 of a linear, first order Autoregressive function, with respect to the replication of its innovation, e. for example: #where e is a random variables of innovation (from GEV distribution-that explains the rgev) #by using the arima.sim model from TSA package, I try to produce Y replicates, with respect to every replicates of e, #means for e[,1], I want

Dear R-helpers, I would appreicate if someone can help me on the transfer parameter in ARIMAX and also see what I am doing is correct. I am using ARIMAX with 2 Exogeneous Variables and 10 years data are as follows: DepVar Period, depVar, IndepVar1 Period, indepVar1, IndepVar2 Period, indepVar2 Jan 1998,708,Jan 1998,495,Jan 1998,245.490 Feb 1998,670,Feb 1998,421.25,Feb 1998,288.170 Mar

Hi, I'm dealing with time series. I usually use stl() to estimate trend, stagionality and residuals. I test for normality of residuals using shapiro.test(), but I can't test for autocorrelation and heteroskedasticity. Is there a way to perform Durbin-Watson test and Breusch-Pagan test (or other simalar tests) for time series? I find dwtest() and bptest() in the package lmtest, but it

Hello, The "arma" function in the "tseries" package allows estimation of models with specific "ar" and "ma" lags with its "lag" argument. For example: y[t] = a[0] + a[1]y[t-3] +b[1]e[t-2] + e[t] can be estimated with the following specification : arma(y, lag=list(ar=3,ma=2)). Is this possible with the "arima" function in the

Hello all, i'm a newbie of R trying to make some statistical work in R environment. Now i have to laptops, one is Thinkpad X40 with Debian Lenny and the other is Thinkpad T43 with Ubuntu 8.10. Recently i met such problem and am wondering if anybody can do some help. After upgrading my /etc/apt/sources.list , i install R by apt-get install command. It works fine in both laptops. Then i

Hello all, i'm a newbie of R trying to make some statistical work in R environment. Now i have to laptops, one is Thinkpad X40 with Debian Lenny and the other is Thinkpad T43 with Ubuntu 8.10. Recently i met such problem and am wondering if anybody can do some help. After upgrading my /etc/apt/sources.list , i install R by apt-get install command. It works fine in both laptops. Then i

Hi, I'm a new user or R and I try to concatenate a several rows according with the value in a column. this is my data.frame and I want to concatenate my data.frame according with the column "b" and make a new data.frame with the information in the others columns. >table1 a b c d 1 E001234 TSA IP234 like_domain 2

I have already fitted several models using R code; arima(rates,c(p,d,q))  As I heard, best model produce the smallest AIC value, but maximum likelihood estimation procedure optimizer should converge. How to check whether maximum likelihood estimation procedure optimizer has converged or not? [[alternative HTML version deleted]]