Try this: > library(forecast) > weight <- as.numeric(weight) > fc <- forecast(weight) > plot(fc)
With this data it chooses a model with multiplicative error and trend and no seasonality. On Sun, Apr 5, 2009 at 2:13 AM, Felipe Carrillo <mazatlanmex...@yahoo.com> wrote: > > Hi: > I have usually used the GROWTH() excel function to do this but now want to > see if I can do this with R. > I want to predict values into the future, possibly with the predict.arima > Function. > I have the following weekly fish weight averages: > > weight <- c("2.1","2.4","2.8","3.6","4.1","5.2","6.3") > week <- c("1","2","3","4","5","6","7") > > I would like to predict what the weight will be by week 10 based on my weight > values and make a line plot of all the weights(including the predicted > values). I have two questions: > 1- Should the predicted values be linear or exponential? > 2- Is the predict.arima function appropriate to do this? > Thanks in advance. > > > Felipe D. Carrillo > Supervisory Fishery Biologist > Department of the Interior > US Fish & Wildlife Service > California, USA > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.