Dec 3, 2017 · Lag is essentially delay. Just as correlation shows how much two timeseries are similar, autocorrelation describes how similar the time series is with itself. Consider a discrete sequence of …

Nov 17, 2023 · What’s the right equation for determining how many of X is needed for Y lagged results when X is normally distributed across a number of days? Ask Question Asked 2 years, 1 month ago …

Feb 1, 2020 · Computation of two covariances between time series (one with both series at same time $t$, one with one lagged time series) Ask Question Asked 5 years, 10 months ago Modified 5 years, …

May 20, 2019 · I am a bit confused about the relation between the Pearson Correlation Coefficient (with time-lag) and Cross-Correlation. I used to think that Cross-Correlation IS the Pearson Correlation …

I am trying to compute the derivative of an experimentally-measured quantity as a function of time. The data are fairly noisy, which causes problems. For instance, using finite differences (central

Dec 30, 2021 · From the paper, and the paper's title even "ZERO LAG (well, almost)", the adaptive filter described in the paper is not exactly $0$ lag. The adaptive filter algorithm is designed to provide a …

I have for some time been trawling through the Internet looking for an aesthetic proof of Taylor's theorem. By which I mean this: there are plenty of proofs that introduce some arbitrary construct...

Data points can likely be modelled as the mean vector plus the covariance matrix times a random vector that's sampled from a standard normal distribution. If that's true, than the maximum variance will be …

Apr 19, 2021 · Your notation $\mathbf {1}$ (or $\mathbf {1}^T$ if you insist that $\mathbf {1}$ is a column vector) is fine and is commonly used. Just define it when you are using it.

Geoff Robertson has written a sketch solution, but my immediate reaction is that this is a standard textbook result, and you would do better to read a book about it rather than trying to do it as an …