All Questions
15,082 questions
0
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1
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30
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Fitting a Nonlinear Mixed Model
I’m trying to fit a nonLinear Mixed Model (nLMM) to test whether the abundance of certain organisms was affected by the sampling period after an event that caused a significant increase.
The data show ...
- 33
1
vote
0
answers
32
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Preprocessing and model selection strategies
I am working on a fault detection problem where each sample is a time series labeled with a specific type of fault. I am using a CNN model and a validation set for hyperparameter tuning. Currently, I ...
- 77
1
vote
1
answer
30
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Identifying Poorly Forecastable Time Series Using tsfeatures
I am working on a problem involving the identification of poorly forecastable time series using features extracted with the tsfeatures library by Rob J. Hyndman. Below are the key details about my ...
2
votes
1
answer
41
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Why can't a non-stationary AR process be represented as an infinite MA process? [duplicate]
Consider the AR(1) process. If $|\phi|<1$, the process is stationary, and we can express the series as
$$ Y_t = \epsilon_t + \phi\epsilon_{t-1} + \phi^2\epsilon_{t-2} + \phi^3\epsilon_{t-3} + \...
- 121
0
votes
1
answer
35
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Best parameter of exponential smoothing when applied on a random walk
Let's say I have a random walk:
$$X_t = X_0 + \sum_{i =1}^t \epsilon_i$$
with the $\epsilon_i \sim \mathcal{N}(0, \sigma^2)$ and independent.
Then what smoothing factor $\alpha$ in an exponential ...
1
vote
0
answers
20
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Regression models that depend on outputs of other regression models
There is a milk factory with the following variables available at the weekly level (i.e. data at the end of each week) and orders are finished on a first in first out basis:
total incoming orders (...
- 141
0
votes
0
answers
14
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Determining how much timeseries relationships are driven by periodicity versus date relationships?
Given three timeseries of monthly data all ending at 11/30/2024 (A beginning at 12/31/2023, B beginning at 3/31/2024, and C beginning at 9/30/2024), one could present the timeseries as 1) aligned on ...
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0
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16
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How to aggregate daily sales data to weekly for thousands of products? [closed]
I have a dataset with daily sales and prices of three thousand products for 5 years and three stores. I want to visualize price and sales trends during weeks of a year. I was thinking of creating a ...
0
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0
answers
21
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Clarifications on Hurst Exponent Definitions and Persistence Properties
I have a question regarding the Hurst exponent that I hope someone here can help clarify.
It is well known that there are different definitions of the Hurst exponent, but finding clear connections or ...
- 1
0
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0
answers
24
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Difficulty in Deriving a Estimator Using Survey Means from Individual Forecasts
I would like to clarify a doubt regarding the paper Testing the Rationality of Price Forecasts: New Evidence from Panel Data (by MICHAEL P. KEANE AND DAVID E. RUNKLE) that presents an estimator ...
- 121
0
votes
0
answers
25
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AIC from sarima vs arima functions in R
I am doing a report of time series, and while analyzing the time series in R, I noticed the using the sarima function
...
- 51
2
votes
3
answers
41
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Testing forecasting accuracy - outliers [ with example]
I have a simple model that produces forecast values. The model works on hourly data. Now, I am only interested in observations with flags. I would like to identify where the forecasts are ...
- 79
0
votes
0
answers
7
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How should I input and output feature and target timeseries to timeseries transformer
I am trying out PatchTST timeseries transformer (paper, code) on a timeseries data that I have. The way PatchTST handles data is as follows:
Note that on line 78-79, the repo does following:
...
- 235
0
votes
0
answers
18
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ACF Diagnostic for Shifted Distribution Univariate Time Series Data
I have these 1920 observations with shifted distribution. For some reasons I want to use all of observations for time series modeling but I have difficulty in reading the ACF plot. I need detail ...
4
votes
1
answer
126
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How to approach time series forecasting
I am working on a time series forecasting problem involving high-frequency data (hourly or every 10-15 minutes), such as energy consumption or other IoT device metrics. My goal is to predict the ...
- 83
3
votes
1
answer
98
views
How to calculate autocorrelation manually
I was taught the autocorrelation in a time-series at lag $k$ is the correlation between all pairs of values separated by this lag.
Suppose I want to give it a go and calculate it manually for lag 1.
...
- 572
1
vote
1
answer
21
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Ecological temporal statistical analysis question
I collected animal samples without replacement over three time periods from the same locality: seven years apart in the deep-sea (eg, no known seasonality). I want to know whether the mean difference ...
- 11
0
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0
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19
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Difference between Rho and Tau statistics in ADF test
I need to check several interest rate time series for stationarity with ADF test, lag = 2.
SAS output generates three types of test statistics: Rho, Tau and F. for three types of test (Trend, Single ...
- 1
3
votes
1
answer
48
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How to best forecast a time series showing level changes and square wave kind of behavior with noise
This is AC power data measured at 1 min interval from March-Dec 2019. I want to model the time series but the out of sample forecast is essentially constant. I found the following from EDA:
Power is ...
- 31
6
votes
1
answer
125
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Is there a way to forecast by subgroup without forecasting each subgroup separately?
I am trying to find an appropriate model to forecast the number of applications received at the end of a recruitment cycle based on previous recruitment cycles and the number of applications received ...
0
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0
answers
8
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Time series - Linear filter model
I was going through the linear-filter-model in Time series.
"Linear Filter Model. an observable time series 𝑧𝑡 in which successive values are highly dependent can frequently be regarded as ...
0
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0
answers
17
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Unable to Extract Pattern from Data from Multiple Devices with Different Distributions
I have been provided with a data set of measurements on the amperage (the only feature) of 3 different Internet of Things (IoT) devices in the form of time series.
Measurements on each device have ...
0
votes
0
answers
18
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Advise to test if two time series are statistically different
I have two time series of paired data (t1 and t2) of dimensions 1x134, obtained by averaging two matrices of 16x134 elements each. I want to study if these two time series (curves) are statistically ...
- 101
1
vote
1
answer
27
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Stationarity Conditions VECM
Suppose we have a vector error correction model (VECM)
$$
\Delta y_{t}=\Pi y_{t-1}+\Gamma_{1}\Delta y_{t-1}+\cdot\cdot\cdot+\Gamma_{p-1}\Delta y_{t-p+1}+u_{t}
$$
A simple way to confirm that it is a ...
- 2,297
2
votes
0
answers
15
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Forecast optimality for categorical dependent variable
I am familiar with several criteria of forecast optimality for variables on a ratio scale. E.g. Diebold Forecasting in Economics, Business, Finance and Beyond introduces the unforecastability ...
- 69.5k
2
votes
1
answer
33
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"Strength" of cointegration
In various non-academic articles/posts, I have come across the claim that the magnitude of the first eigenvalue in Johansen's cointegration test for a pair (pairwise test) might indicate the "...
- 123
7
votes
1
answer
71
views
+50
Why don't we typically worry about stationarity in panel data models with fixed effects?
Why don't we typically worry about stationarity in panel data models with fixed effects?
In time series analysis, stationarity is often a crucial assumption. However, I've noticed that in applied ...
- 229
1
vote
0
answers
13
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Dealing with non-stationary time series in Granger Causality
I am working on determining the Granger Causality of two time series.
One thing to note is that for my specific project, I have around 100k time series across two different dimensions, say Product ...
- 391
3
votes
2
answers
207
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Why are the HAC (Newey-West) standard errors smaller than the ordinary standard errors in my regression? [duplicate]
I used time series to perform a regression, and then I conducted the Breusch-Godfrey (BG) test and the White test. The test results indicated the presence of both autocorrelation and ...
- 41
0
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0
answers
16
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Embeddings in time series prediction
Increasingly, I’ve noted that embeddings are used in pure prediction ML tasks. For example, instead of predicting whether user i will purchase item i and thereby adding thousands or millions of inputs ...
- 3,520
0
votes
1
answer
20
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Problems with using ACF and PACF for ARMA modelling
This is the ACF and PACF for my the first difference of my variable $\Delta y_t,$ I used the ADF test, the PP test, the Schmidt Phillips test and the DFGLS test, and got the same result that my ...
- 1
0
votes
0
answers
10
views
Conflicting results in DF and ADF tests
I am conducting unit root tests on the globtemp dataset, which is clearly a series with a trend and some seasonality (not stationary). However, when applying the ...
2
votes
0
answers
34
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How Are The Initial Value of Conditional Variance Calculated in rugarch Package?
I am trying to verify the calculations of my zero-mean GARCH(1,1) model using the rugarch library. At first I thought the initial first value of the conditional ...
0
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0
answers
18
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How to Forecast Sales for Sub-Locations Without Historical Proportion Data?
I have a time series dataset of total sales for a product in a store over time. This product is available in two different locations within the store: one stand near the checkout and another stand in ...
0
votes
0
answers
28
views
LSTM Limitations for Time Series Forecasting
I am working on a project where I generate synthetic data which is the sum of 5 random sine functions sampled every 0.01s (and I add mean reverting brownian motion noise to the data).
...
0
votes
0
answers
22
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Forecasting Multiple steps of a Multivariate Time Series for ALL Features
I am working on a project where I have 100 multiple time series of length 1-10 minutes (samples every 0.1s). Each time series is a recording of human emotions stored as a vector of 7 features with ...
4
votes
1
answer
42
views
Uncertain serial autocorrelation in GAM count model residuals
I wish to use Generalised Additive Models (GAMs) to smooth count time series and estimate first derivatives, i.e. to identify periods where the counts are increasing, stable or decreasing.
I'm using R ...
- 509
1
vote
0
answers
20
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Time Series Analysis - AR model
I am new to the subject and trying to learn and equip well into the topic. I got a problem to solve and it only contains the model equation - {Generic AR(N) model} modelled using the equation: v[k] + ...
0
votes
0
answers
7
views
How do I account for replicates at the same sites when looking for spatial autocorrelation?
I am trying to examine the effect of spatial patterning/autocorrelation on a response variable at a number of sites distributed unevenly across a landscape (probably using Moran's I) but I'm unsure ...
0
votes
0
answers
12
views
Data augmentation for Bootstrapping low-variance data
I am working on local block bootstrapping of student right/wrong (0,1) data from an online learning tool. Note. (local block bootstrapping creates moving blocks of responses but sets guardrails on ...
0
votes
0
answers
14
views
Under which conditions does PCA consistently estimate latent factors in a Dynamic Factor Model?
Consider a dataset of N time series and T observation periods.
Assume each series $x_t$ is generated from a single (unobserved) common factor $f_t$ following this model:
$$
X_t = \Lambda f_t + \...
1
vote
0
answers
44
views
Creating a non-homogenous queue based on another statistical model?
I have a question on how construct/approximate a statistical queue based on changing parameters.
I created/simulated this approximate version of a MMK queue in R:
...
- 667
2
votes
1
answer
34
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Fitted values of initial observations in auto.arima for non-stationary models
If I understand correctly, the fitted values returned in the auto.arima of the forecast R package are the one-step ahead forecasts given by the model, once the ...
- 151
1
vote
0
answers
16
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Time series decomposition on discontinuous data
I have a activity interevent time data like this:
...
- 63
0
votes
0
answers
27
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Comparing different timepoints of measurements (1,2,3,4) for a group of individuals who survived vs. not survived
In most cases we have a time series based measurement (CD8T) for a group of individuals who survived or not survived (Survival) from a disease (repeated measurements). The timepoint based measurements ...
0
votes
0
answers
39
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Is my time course analysis with DESeq2 valid?
As a pure behavioural ecologist who has stumbled into the world of gene expression analysis and am a novice in analyzing it, I am asking for help in validating whether my model is correct for the type ...
1
vote
0
answers
17
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Degrees of freedom for Ljung-Box test
I have two questions regarding the degrees of freedom for the Ljung-Box test on residuals in case of different AR(p) models:
In case of a model with non-consecutive lags: As I understand it, one has ...
- 11
0
votes
0
answers
12
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Calculation in Prediction for an MA(1)
When we calculate $\theta_{n1}$, why does the summation in $(3.79)$ become zero?
$$\theta_{t, 1} = \theta_{t, t-(t-1)}= \frac{\gamma(1) - \sum_{k=0}^{t-2} \theta_{t-1, t-1-k} \theta_{t, t-k} P_{k+1}^k}...
- 123
0
votes
0
answers
24
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Model Stacking - Out of Fold Procedures
I am attempting to use a model stacking procedure where I am using a time-series split on a set of data I have (around 5000 entries). The goal is binary classification.
After obtaining hyper ...
- 47
0
votes
0
answers
18
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Comparing data at different locations over a time series
I have water quality data from sondes placed at different locations across a lake that collected every hour over the entirety of the summer. I want to know if there is a difference between the four ...
- 1