Forecasting time series using R

Published on 27 October 2011 in Talks

Mel­bourne R Users’ Group
Thursday, Octo­ber 27, 2011, 6:00 PM
Deloitte, Level 11 (Cul­ture Room), 550 Bourke Street, Melbourne

I will look at the vari­ous facil­it­ies for time series fore­cast­ing avail­able in R, con­cen­trat­ing on the fore­cast pack­age. This pack­age imple­ments sev­eral auto­matic meth­ods for fore­cast­ing time series includ­ing fore­casts from ARIMA mod­els, ARFIMA mod­els and expo­nen­tial smooth­ing mod­els. I will also look more gen­er­ally at how to go about fore­cast­ing non-​​seasonal data, sea­sonal data, sea­sonal data with high fre­quency, and sea­sonal data with mul­tiple fre­quen­cies. Examples will be taken from my own con­sult­ing exper­i­ence. I will give an over­view of what’s pos­sible and avail­able and where it is use­ful, rather than give the math­em­at­ical details of any spe­cific time series methods.

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