Questions tagged [moving-window]

A window is a fixed-length subset of consecutive observations of a time series. The window is moved along the time series at a constant rate. Also known as "rolling window".

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Deciding Rolling mean and standard-deviation Window of a Time-Series Distribution

I have a Daily time-series data of 6 years. And I need to do Weekly forecasting on this Daily-basis data. Before forecasting, I want to find rolling mean & STD to determine the stationarity of ...
53 views

ARIMA + Rolling Window

I'm currently working on building an ARIMA+GARCH model using R. My dataset consists of the logarithmic returns of the Dow Jones index for a period of 11 years 2005-2016, however, it's worth noting ...
21 views

How to estimate policy impact using interrupted time series, when outcome variable is a moving average?

Suppose you want to evaluate the impact of a recently implemented policy using interrupted time series because you have no comparison group and the policy was implemented all at once on the ...
24 views

How does the sliding window work?

I am not sure how the "Sliding window" method work. Let's assume I have a dataset of number of logins by hour. a) A window of 24hours to predict the next 24h? b) A window of 24h to predict the next ...
45 views

What is the difference between a discrete and continuous rolling window?

What I have read so far suggests that a discrete rolling window is say a yearly window, calculating somethig every year, which is from 01-01/31-12 and a continuous rolling window is a window that ...
120 views

LSTM - When to use sliding window in time series classification?

Say I have a tensor of data with shape (30, 16000, 38) - where each tuple element corresponds to ...
95 views

How to compute the change of Ridge regression solution when one row of data changes?

I understand that $\boldsymbol{\beta} = (X^TX + \lambda I)^{-1}X^T\mathbf{ Y}$ is the closed form solution of Ridge regression. So sometimes, when I run a rolling window, meaning everytime I run the ...
73 views

Is it fair to consider rolling regression a form of bootstrapping?

The context is time series analysis. A few similarities between rolling regression and boostrapping jump out at me, in that both re-use observations to form new subsamples for estimation. However, ...
38 views

Constructing signal vector of EWMA

I have daily stock returns related to sectors. At the end of each month I want to construct a vector of signals using the past data with different methods over different moving windows like EWMA over ...
123 views

How to make predictions on sliding window?

I need help understanding how to construct sliding windows as well as how to perform final prediction. Any help is appreciated! I have a dataset from sensing data with multiple features aggregated ...
810 views

What is rolling mean and standard deviation in terms of stationarity?

I would like to know what a rolling mean and rolling S.D means in terms of achieving stationairty concerning a time series? I ran an ADF test and it told me my time series was stationary however, by ...
39 views

Classify time series with unequal lenghts [closed]

I have a set of time series sensor measurements (acceleration and gyroscope readings) for driving events (harsh acceleration, harsh brake …) with the type, start and end of each event. I need to ...
17 views

Is it possible to make LSTM model with 4dimension shape?

Hellow, wizards. I have time series data including sevaral days. I try to predict a grade of tomorrow, which is range from 0 to 100. And I assume that this grade depends on 3 time-series independent ...
28 views

Average time series forecast errors from cross-validation with rolling origin

I'm calculating the MAPE and RMSE over a rolling origin cross-validation with fixed forecast interval for several models. For example, for a daily series with 3 years, I'm training my model with 2 ...
33 views

Difference between historical, performance and Observation window

I have taken up a logistic regression course on Udemy and the trainer is from India. He has talked about differences between historical, performance and Observation window. However, it is very ...
121 views

Rolling Window Forecasting with ARIMAX while supplying actual values

I am comparing different exogenous variables in how good they support the forecast of the monthly seasonal adjusted unemployment rate. All my data is monthly (2006-01-01 until 2018-09-01) and ...
814 views

How to decide moving window size for time series prediction?

I have a model to predict +1 day ahead of this time series. Looking at the chart you can notice some seasonality every 5 days. I suspect using a moving window as training set could help me making a ...
81 views

DNN methodology and feature concatenation

I'm using someone else's job and I have a question that I cannot solve. This work uses a DNN to match an electrical resistance to a bend angle. This is not very important, just for the context. So,...
138 views

Impact of window size on estimated volatility using SMA or EWMA

When calculating volatility (either using an SMA or EWMA approach), what impact does the window size have on the volatility estimate?
119 views

Markov Switching GARCH - Expanding or Rolling window forecasting?

When modelling volatility do people tend to use expanding or sliding windows to predict the performance of MS GARCH models?
86 views

Rolling sum of 2 sample KS test results

In order to compare two lists of samples from 'before-treatment' and 'after-treatment', I am doing a two sample KS test using the ks_2samp function from Python's scipy.stats package which gives me the ...
180 views

Moving window time series

I am working on some computations for large datasets of market data and I was wondering is there is a simple way to apply the following logic without using heavy looping. I will simplify the problem: ...
34 views

Using a recoded window 10 days back in a GAM-model, is that a double whammy or is it OK to do?

I'm formulating a prediction in a logistic reression type in a GAM model. ...
476 views