# Intuitive explanation of state space models

Having looked into options for modelling and forecasting a financial time series based on mixed frequency data, I came across state space models, which seems worth exploring.

I've however been unable to find a clear, intuitive and largely un-mathematical explanation of how a state space model works or what they do to allow mixed frequencies.

As all the info I have found on this topic seems very technical I, and hopefully others, would very much appreciate some clarification on what seems to be a pretty powerful tool.

Some tools like R's bsts package make it more accessible, but it's fundamentally more complex than alternatives. Not that you should be using ARIMA or other methods without some level of technical sophistication, but in my experience most state space (also called dynamic linear model) packages have gaps where you'll need to know what parts of various matrices represent and mean.
And if you use R, you should check out bsts.