What is frequency for daily data?
Daily data There could be a weekly cycle or annual cycle. So the frequency could be 7 or 365.25. Some of the years have 366 days (leap years). So if your time series data has longer periods, it is better to use frequency = 365.25.
What is hourly seasonality?
Hourly data usually has three types of seasonality: a daily pattern, a weekly pattern, and an annual pattern. Even weekly data can be challenging to forecast as it typically has an annual pattern with seasonal period of 365.25/7≈52.179 365.25 / 7 ≈ 52.179 on average.
Which is better to use monthly or quarterly data?
You have monthly data, so it’s a waste of data not to use it at its native frequency. It doesn’t look like you have millions of observations to waste. Instead, it’s better to up sample the quarterly data. Convert your quarterly series into monthly setting the quarterly values the same for all three months of each quarter.
How to calculate the frequency of a seasonal period?
Similarly, data that are observed every minute might have an hourly seasonality (frequency=60), a daily seasonality (frequency=24×60=1440), a weekly seasonality (frequency=24x60x7=10080) and an annual seasonality (frequency=24x60x365.25=525960). If you want to use a ts object, then you need to decide which of these is the most important.
Which is better monthly or quarterly reset frequency?
Recently, when I’ve had the chance to listen to insurance company annuity wholesalers pitch their variable annuity riders, I’ve been hearing much ado about “reset frequencies” and the relative benefits of monthly vs. quarterly or daily vs. annual adjustments.
How many days are in a time series?
I have two large time series data. One is separated by seconds intervals and the other by minutes. The length of each time series is 180 days. I’m using R (3.1.1) for forecasting the data.