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Questions tagged [multivariate-time-series]

96 questions
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Time Series Analysis: Forecasting of categorical variable(s)

I have a machine's fault(s) occurrence data (in terms of 0 & 1) with respect to 1 minute time intervals. 0 stands for no fault occurred and 1 stands for say a particular fault occurred. So continuous 0's means no fault occurred in a time duration…
Siddhartha Saha
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Using Sktime Regressor

I am trying to use any regressor model from sktime but but I couldn't figure out how to create the data type and format I need to use. Assume I want to use 2 columns as input and 1 column as target. from sktime.regression.interval_based import…
Mert Arda Asar
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Multi covariate time series forecast using Darts

I am trying to use the tutorial here, where we have two covariates to predict the target. The tutorial uses .stack() to add two covariates together. It is not clear to me how to use this function to add more than two covariates to the model. I tried…
M.M
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Rbeast Time Series - Weird Time Axis In Plot

I am looking into ambient air pollution within regions of NSW and conducting a daily time series decomposition analysis using Rbeast to investigate if there is a change point signature around the time of Covid-19 lockdowns. I have created a looping…
Hannah0575
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Problems with inverse_transform scaled predictions and y_test in multi-step, multi-variate LSTM

I have built a multi-step, multi-variate LSTM model to predict the target variable 5 days into the future with 5 days of look-back. The model runs smooth (even though it has to be further improved), but I cannot correctly invert the transformation…
Luca
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Casual inference between a multi-dimensional time series and univariate time series (in python)

Trying to produce a causal relationships between data sources (e.g. A -> (cause) B), I could find a lot of sources for casual inference between univariate signals (e.g. temperature and speed). Nevertheless, I have hard time to find a way to test if…
Α Πι
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Combining CNN and LSTM for multivariate and multi-step time series forecasting

I'm trying to build a CNN-LSTM model for multivariate time series multi-step forecasting. The input is (2000 x 4) where 4 is the number of columns in my dataset. I got this error: ValueError: Shapes (None, 4) and (None, 1) are incompatible this is…
Mouna Ahmen
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Checking chunks of names in column of pandas dataframe for completeness

i have a pandas df that includes columns of sensor measurements were each row contains the sensor measurements of one unique sensor node. The order of these rows from the sensor nodes looks like this: {{0: 'sensornode0009', 1: 'sensornode0015', 2:…
pascal_
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Find recursive pattern on multivariate binary time series

I need to find recursive pattern on binary time series (on 3 channels). TS sample data: channel1_data = [0, 1, 1, 0, 0, 1, 0, 1, 0, 0] channel2_data = [0, 0, 0, 1, 1, 0, 1, 0, 1, 0] channel3_data = [1, 0, 0, 0, 0, 0, 0, 0, 0, 1] pattern I want to…
user3925023
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How to determine the most significant predictors - multivariate forecasting

I would like to create a forecasting model with time series in R. I have a target time series 'Sales' that I would like to forecast. I also have several time series that represent, for example, GDP or advertising spend. Unfortunately I have a lot of…
Timo
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How to train an LSTM model on multiple smaller individual datasets?

I have 11000 datasets each having 52 entries corresponding to 52 weeks of data. I want to train a single LSTM model on all these 11000 datasets, as I feel that individually training the data on a single dataset, and predicting for every dataset will…
imaybedumb
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Multivariate LSTM cross feature dependencies

I was working myself through handson-ml2, and chapter 15 in particular. I want to generalize the multiple steps ahead approach to multiple features and one target. In order to test my understanding I create some series, which are either following a…
Tha_X
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Can `mvabund::traitglm()` handle random effects?

I am using the R package mvabund to examine how environmental conditions and species traits are correlated with ecological community structure. The traitglm() function is a nice tool for this. However, my data consist of ~40 'sites' repeatedly…
Joshua Smith
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curve_fit multivariable arrays non-linear regression

I am trying to fit the coefficients of a multivariate function with curve_fit. All variables are arrays of the following shape : (1000,) Manually I can fit the curves as follows. First I define my function where the variables =…
Carlos Raymundo
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MVGC F value and P value calculation

I am currently working to find Multivariate Granger Causality F value and p value via this code. def demean(x, axis=0): "Return x minus its mean along the specified axis" x = np.asarray(x) if axis == 0 or axis is None or x.ndim <= 1: return x -…
13LUE parang
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