9 votes
Accepted

Significant bias introduced into simple simulation

You have fallen victim to the renewal paradox, a.k.a. inspection paradox, a.k.a. length-biased sampling. $F_{\Delta}$ is the distribution of service time for the kth customer, but it is NOT the ...
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8 votes
Accepted

Meaning of Moving Average Term in ARIMA

For time series, it is better to think about the $\alpha_t$ terms (supposed to be an independent mean zero series) as innovations, not errors. They are not modeling errors of measurements, but the ...
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7 votes

How to handle many time series?

If the 1200 products are closely related, so that trend (if any) and noise are likely to be correlated across products, a single model might make sense. If they are loosely related (so that they might ...
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  • 28.7k
5 votes

How to handle many time series?

This problem is a multivariate (simply when you have more than one time-dependent variables) time series for which you can use Vector Auto Regression (VAR) technique among some others. Explanation and ...
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  • 8,185
4 votes

Significant bias introduced into simple simulation

Note: This answer is intended to show what I have learned from the valuable answer provided by @Mark L.Stone. His post answered my question of why the simulation is biased. Hence, this post provides ...
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4 votes
Accepted

Approximately evenly-spaced subsequence

I have never encountered a problem like this in literature, but here is one possible way of formulating the problem as a MIP. Notation: $n$: length of the number series $l$: desired length of the ...
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4 votes

How to handle many time series?

The demand of 1200 product will often be related. There might be common events (Christmas, some large accident, ...) that influence all or many of the demands, substitution effects, ... or there may ...
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4 votes

Meaning of Moving Average Term in ARIMA

Kjetil's answer is very good, and the distinction between errors and innovations are important to understand. But there are also applications where measurement issues do result in MA-type errors. For ...
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