similar to: Arima forecasting

Hi, I tried to use the Croston function from the forecasting package 1.24<http://robjhyndman.com/software/forecasting> with the code below, but I get in return this message "*Error in decompose(ts(x[1L:wind], start = start(x), frequency = f), seasonal) : time series has no or less than 2 periods*". histValues

I'm testing some modifications in arima.c. I've noticed that a big internal array of double (rbar) is usually sparse and I'd like to add an option to store it as key-value mapping. Is there a library function or some other approach already used inside the R core for key-value mappings? Thanks, Matteo Bertini

I am using AUTO ARIMA for forecasting. But it is not detecting 'seasonality term' of its own for any data. Is there any other method by which we can detect seasonality and its frequency for any data? Is there any method through which seasonality and its frequency can be automatically detected from ACF plot? -- Siddharth Arun, 4th Year Undergraduate student Industrial Engineering and

Hi, I would like to create variables in R containing parameters of summary(*Forecast Results*). Using the following code: library(forecast) data <- AirPassengers xets <- ets(data, model="ZZZ", damped=NULL) xfor <- forecast(xets,h=12, level=c(80,95)) summary(xfor) the output is: Forecast method: ETS(M,A,M) Model Information: ETS(M,A,M) Call: ets(y = data, model =

Hello! I have such a problem... Estimated a model based on common data (you can find it in R library), and I wanted to plot the orginal values with the estimated one. Unfortunately I can only see the original values. Below is the code with data library: / library(forecast) data(AirPassengers) AP <- AirPassengers class(AP) start(AP) end(AP) frequency(AP) lgAP <- log(AP) t<-2:length(AP)

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

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, When I run this code a part of my x-axis and y-axis changes color. Can somebody tell me what is wrong? Also, is there a way to control the color of the average lines? monthplot(AirPassengers+500, ylim=c(min(AirPassengers), max(AirPassengers+500)), ylab="") par(new=T) monthplot(AirPassengers, col="blue", ylim=c(min(AirPassengers), max(AirPassengers+500)),

Hello, I'm an R newbie. 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

data(AirPassengers) brings AirPassengers into the workspace. How can I  idenfity what the structure of AirPassengers is? Is it a data.frame, a table etc. etc. [[alternative HTML version deleted]]

Hi, i want to construct a data set similar to "AirPassengers". Its attributes are following. > attributes(AirPassengers) $tsp [1] 1949.000 1960.917 12.000 $class [1] "ts" How Can I construct a data set similar to it having same class and attributes. Thanks -- Amar Kumar Nandan ?:nandan.amar at gmail.com http://aknandan.co.nr

Greetings: I'm using the time series decomposition routine "stl" from the package "stats". But how do I get the results into a vector to work with them? example: data(AirPassengers) m<-stl(AirPassengers,"per") print(m) This lists the output but can't figure out how to extract the individual series like seasonal, trend, irregular. Thanks, Bob

Given: data(AirPassengers) I get a ts data structure AirPassengers in the workspace. How can I generate the code that can create that structure? That is, given an example of a data structure, is there a way to generate the code that can greate that structure? Alternatively, is there a reference that provides a list of dta structures together with a full list of theor respective attributes?

Hi guys! I'm new to R, but I was wondering if one could plot many histograms into a single graph each having a different color. To make things clear: Suppose you have a matrix of 100 rows and 10 columns. I'm interested in plotting the histogram for each row, but it should not appear as bars but rather as lines connecting the points of the frequencies. Now, I want to do this for the 100

Hola usuarios, Necesito detectar si existe o no un cambio de tendencia y si dicho cambio es significativo, para una serie temporal del tipo AirPassengers, en la que a partir de un determinado momento se ha hecho una campaña (supongamos que una promoción de vuelos). Para ello he pensado varios métodos: Usar la descomposición espectral de la muestra [decompose(AirPassengers)] y luego una Regresión

Hello, In order to do a future forecast based on my past Time Series data sets (salespricesproduct1, salespricesproduct2, etc..), I used arima() functions with different parameter combinations which give the smallest AIC. I also used auto.arima() which finds the parameters with the smallest AICs. But unfortuanetly I could not get satisfactory forecast() results, even sometimes catastrophic

Hello everybody! I'm having this problem with the auto.arima function that i've not been able to solve. I use this function on time series that contains NA values, but every time that the resulting model contains drift I can't perform a forecasting (using forecast.Arima function). The printed error (when I try to forecast the resulting model) claims a dimension mismatch

It''s possible merge two or more cell ??? ex: -------------------------------------- | LABEL 1 | LABEL 2 | LABEL 3 | -------------------------------------- | VALUE CELL MERGE | ANOTHER | -------------------------------------- | | | | -------------------------------------- Many Thanks Carlo Bertini www.waydotnet.com -- Posted via

I'm currently working with some time series data with the xts package, and would like to generate a forecast 12 periods into the future. There are limited observations, so I am unable to use an ARIMA model for the forecast. Here's the regression setup, after converting everything from zoo objects to vectors. hire.total.lag1 <- lag(hire.total, lag=-1, na.pad=TRUE) lm.model <-

Hello, I just ran the predict.StructTS function using the AirPassengers data and got a ridiculous result. Here's what I ended up with: http://24.210.155.111/PredictWhat!.pdf Who wrote this? Am I seriously supposed to think this function would accurately predict a time series? -AnalogKid