On this website, Mr. Davenport published a function to plot an arima forecast with ggplot2 on the example of an arbitrary dataset, he published here. I can follow his example without any error message. Now, when I use my data, I would end with the warning: 1: In window.default(x, ...)...

I have an ETS(M,Md,N) model and would like to write it in state space form: yt=w(x{t-1})+r(x{t-1})ɛt xt=f(x{t-1})+g(x{t-1})ɛt For additive trend, the state vector xt=(lt,bt)'. But I have no idea how to write the state vector xt for multiplicative trend. Can anyone help please:D...

I am trying to generate a 1-step-ahead forecast of a quarterly variable using a monthly variable with the midasr package. The trouble I am having is that I can only estimate a MIDAS model when the number of monthly observations in the sample is exactly 3 times as much the...

I have a small time series dataset, a sample of which is below: year AvgU5MR AvgPov AvgEnrol 2000 126.9307 41.0109 67.11833 2001 123.4138 39.9748 68.66798 2002 119.93 45.85194 65.82739 2003 116.4923 55.3706 69.17756 2004 113.1362 32.63662 70.83884 2005 109.9008 41.08603 75.35649 2006 106.816 43.45722 75.98755 2007 103.8878 19.19114 76.86299 2008...

I'm working on a time series forecasting problem and I would like to confirm if it makes sense to compute the standard deviation of the root mean squared error. If so, is this the correct way? STD_test = std(sqrt((y_real-y_pred).^2)) Also, imagine that the output of the model is 100, the...

I have created a list of 300 time series. Now I want to create a training sample(by holding out most recent 3 weeks) for each of the time series to build forecast models. So I want to use window function to subset the time series to skip the most recent...

I am working on making a prediction in R using time-series models. I used the auto.arima function to find a model for my dataset (which is a ts object). fit<-auto.arima(data) I can then plot the results of the prediction for the 20 following dates using the forecast function: plot(forecast(fit,h=20)) However...

I have a hierarchical time series, the bottom level series of which all exhibit intermittent demand. It seems advantageous to use Hyndman's HTS package for optimal combination within the hierarchy. It also seems advantageous to use Kourentzes' MAPA package for multiple aggregation prediction of the intermittent demand. In essence, I...

I am using ets() function in R to fit the seasonal model.I have a weekly sales data.I can see clearly in my data that it has seasonal patterns along with trend. Following is the code: x_ts<-ts(x,frequency=52,start=c(1,1)) nfit <- ets(x_ts,damped=FALSE) Is it because I have used damped=FALSE in my model? I...

I'm working on building a Shiny App for forecasting time series. One component of this is using ARIMA models to forecast. The user specifies the start and end of the historical data, what p, d, and q they would like to use in the ARIMA model (if they don't want...

Is it possible to predict directly into the future using epsilion-svr? My dataset is a univariate time series and has per line a record in this format: Y(t-W), Y(t-W+1), ..., Y(t), Y(t+PH) W is the number of time steps to consider PH controls how many steps into the future I...

I'm using a forecast function in R many times with loop (12 months) for but I want to use accuracy to compare forecast for horizon time =12 and one-step ahead. My problem is how to store the results of 12 times to use it in accuracy. for (i in 1:12)...

It appears that arima.errors() ignores any Box-Cox transformation that may have been included in the model. Here's a quick example. library(forecast) set.seed(1) xreg <- ts(4 + rnorm(150)) transformed <- 2 + 0.4 * xreg + arima.sim(list(ar=0.6, ma=c(-0.2, 0.3)), n=150, n.start=50) y <- InvBoxCox(transformed, lambda=0.5) fit <- auto.arima(y, xreg=xreg, lambda=0.5, stepwise=F,...

I am trying to pass xreg arguments in my forecast but keep running into an error which says: fc=forecast(gy,fmethod="arima",h=days,method="bu",xreg=z,newxreg=fz) Error in as.matrix(newxreg) %*% coefs : non-conformable arguments In addition: Warning message: In cbind(intercept = rep(1, n), xreg) : number of rows of result is not a multiple of vector length...

I've been doing a variety of models in R with time series data (in XTS format) and I keep running into the same issue where there's no date / time component to the fitted values / forecasts and thus I can't graph them on the same graph as the original...

I Want to compute the accuracy of a numerical vector that contains 12 forecasts but I get this result with a warning. `> accuracy(f,Test) ME RMSE MAE MPE MAPE ACF1 Theil's U Training set NaN NaN NaN NaN NaN NA NA Test set 0.9064933 0.9064933 0.9064933 0.4060658 0.4060658 NA NA...

I am using RRDTool to graph Data and a predicted Trend (LSL) in one Graph. Therefore I am adjusting the corresponding template. At the moment I set my end time like this: --end start+7d When looking at the resulting graphs via the website I can select different time ranges on...