"rolling window" is correct and usable in written English.
You could use it to refer to a technique used to smooth out the peaks and valleys of data points, i.e. a technique that breaks up a dataset into multiple sections and performs some kind of calculation on each section. For example, "The analyst used a rolling window to smooth out the stock prices over time."
A new rolling window optimization method is presented, where the global optimization problem is decomposed into small optimization sub-problems, which are defined on a series of successive rolling windows.
To prevent possible structure breaks in the time series of the NS parameters, for the case of the 1 year horizon, the daily predictions were conducted recursively using a 5-year overlapping rolling window.
Using two metrics, area of the receiver operating characteristic curve (AUC) and area of the LIFT cumulative curve (ALIFT), the four models were tested on an evaluation set, using the most recent data (after July 2012) and a rolling window scheme.
If τ denotes the length of the rolling window, then the error term ϑ it follows a normal distribution function: Nleft 0,{sigma}_tleft tauft(tau right kern0.5em mathrm{with} {w}_tleft tau right)=frac{1}{sigma surd left(2varPi right) } expleft -frac{{left tau -tright)}^2}{2{sigma}^2}right), tau in lexpleft -frac{{left tau) (2).
In order to show how the potential outliers can mislead the detection of the leverage effect, as measured by the cross-correlations between past and squared returns, we use a rolling window scheme, where the sample size used to compute the cross-correlations is (T=1000).
The thermal stress on corals is estimated using the accumulation of "degree heating months" (DHMs) over a four month rolling window.
Proposed rolling windows of static recrystallization (SRX) and non-recrystallization were determined for industrial plate rolling.
The issues examined include series-splitting rules, fixed versus rolling origins, updating versus recalibration of model coefficients, fixed versus rolling windows, single versus multiple test periods, diversification through multiple time series, and design characteristics of forecasting competitions.
We computed a minute-by-minute integrated CRI risk score based on the method described in [1], using features computed from VS data streams during trailing 15 minute rolling windows and a trained random forest machine learning model.
The approach is based on a mixed-integer-linear-programming formulated over a rolling horizon window, considering predicted future electricity load demands and renewable energy generations.
There isn't a big fix for all of our problems, but there are little ones like taking someone that you love on a drive, rolling the window down and putting on your favorite song.
