All Questions
16,349 questions
1
vote
1
answer
62
views
Estimation of model coefficients of ARIMA model
Let say I have below ARIMA model estimation in R
...
2
votes
0
answers
19
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Hierarchical models where the hierarchy structure depends on a latent variable
I am having trouble formulating a hierarchical model for the purpose of Bayesian inference in the case where the actual hierarchical structure depends on a latent variable. I am wondering if this is ...
1
vote
0
answers
14
views
What are the pros and cons of using multivariate Filtered Historical Simulation with univariate GARCH models compared to a GARCH-DCC approach?
I am assessing the market risk of an equity portfolio and have come across an example in the MATLAB documentation that uses a multivariate Filtered Historical Simulation technique:
https://it....
2
votes
0
answers
39
views
Can I Perform a Micro Synthetic Control Analysis with Different Aggregation Levels for Treatment and Control Groups?
I am conducting an analysis using the microsynth package in R to evaluate the impact of increased police presence on various outcome measures obtained from an official survey. My treatment areas ...
1
vote
1
answer
47
views
Time-series forecasting problem in Python
I am working on a Python project where I have to predict the energy consumption in individual households. My dataset consists of several thousands of households each having a monthly value of the ...
0
votes
1
answer
38
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Separate XGBoost Models for Multiple Time Series
I'm getting data by connecting to database to get electricity consumptions. In my case there are lots of meter id's (they will increase to thousands in time) and each meter id has its own time series ...
2
votes
1
answer
66
views
ARIMA Model Forecasting - 95% Prediction Intervals
I'm currently learning about time series forecasting and ARIMA models. For this question, I'll just be using the AR(1) model example $X_t = \phi X_{t-1} + \varepsilon_t$ and say we are forecasting $X_{...
0
votes
0
answers
11
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Fitting nonlinear Bayesian regression with a summation term in brms
I'm trying to fit parameters for a Holling type II curve for multiple prey items. This takes the form:
$$
\frac{dP_i}{dt} = \frac{a_iP_i}{1 +\sum_j{a_jh_jP_j}}
$$
where $P_i$ is density of prey ...
1
vote
1
answer
41
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Question About Approximating the Variance of the Sample Mean for an AR(1) Process
$
\newcommand{\on}[1]{\operatorname{#1}}
\newcommand{\ol}[1]{\bar{#1}}
\newcommand{\Cov}{\on{Cov}}
\newcommand{\Var}{\on{Var}}
$
Problem Statement: Suppose that the time series data $\{x_i:i=1,\dots,N\...
1
vote
1
answer
45
views
Persistence of the sum of two AR(1) Processes
Consider a time-series, $y_t$, that can be disaggregated as the sum of two component parts:
$$y_t = x_{1,t} + x_{2,t} $$
Suppose that each of the component parts is independent and follows a ...
1
vote
1
answer
26
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Setting predictor variables with 3-levels in multilevel mode
I am working with a random intercept multilevel modeling.
I want to predict general health based on survey data. The survey uses nested data set on three levels: individual, county, and state.
I am ...
1
vote
0
answers
16
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Unit-invariant treatments in panel data
Beginner with a beginner question about two-way fixed effects. I'm using R, if that's relevant.
Like the user in this question, I'm interested in estimating how time-varying (but unit-invariant) macro ...
3
votes
1
answer
48
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Mixed Model: Translation from mathematical notation to R's lmer() - package: lmerTest
The following data should be generated and fitted to a mixed model (for further simulation studies):
$y$: outcome of clinical study (effect of medication)
indiv individuals = 20
repl replicate ...
0
votes
1
answer
33
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Treatment effect estimation for policy change in time series
I have time series data and want to estimate the impact of a policy change on an outcome. The policy comes into effect at some point and remains active for the rest of the sample period. So I only ...
1
vote
2
answers
35
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About adding random effects in Multilevel (HLM) analysis
I am doing regression analysis in HLM. I am wondering whether random effects should be added in this process.
Let me ask a question using a famous example. LV1 is a student and LV2 is a school. LV1 ...
0
votes
2
answers
54
views
How to model a discontinuous Time Series with two or more "components"?
Suppose a time series clearly has two or more “components”, e.g. a “zero” component and another one that looks like a continuous series. Example:
Suppose we can’t find covariates that can explain why ...
2
votes
1
answer
35
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Experimental condition with multilevel model
I am working with a survey experiment. The data is set at three levels: individual, county, and state.
The experimental condition was randomized at the individual level 1. That is, some individuals in ...
0
votes
0
answers
63
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non-negative constraints and interactions in the ensemble model
In the context of prediction problems using regression models, suppose I have $K$ different models all trained (fitted) on the same targets (observations). These models are different - low correlation ...
0
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0
answers
12
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Feature scaling for time series when only feature is lagged demand qty
When building a time series model, if the only feature I am employing is lagging the target variable, should I still scale everything? Or would it not necessarily matter?
0
votes
1
answer
64
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Does including a variable for stepwise change and another variable for linear change in an ARIMAX model introduce issues of multicollinearity?
I am trying to perform interrupted time series analysis using an ARIMA model based on the following paper: Interrupted time series analysis using autoregressive integrated moving average (ARIMA) ...
1
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0
answers
28
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What are the appropriate data splitting techniques for time-dependent sequential datasets, such as breakdown records over time?
I am working with a time-dependent sequential dataset, specifically a record of machine breakdowns over a period of time. My dataset includes data from the sensors of several machines until they fail ...
0
votes
1
answer
43
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Sampling a binary time series and estimating proportion of 1s - why is the error less when the time series has longer contiguous regions
I've been messing around with a dataset that can be abstracted to a binary time series. That is to say a series of values that can be either 1 or 0, each representing a millisecond of time.
I am ...
0
votes
0
answers
11
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Not able to perform an ANOVA test with a time series objects due to different residual lengths (R)
I am performing a general-to-specific procedure. I want to check the joint significance of all the insignificant variables.
I have a general model with all the variables, none removed, a model_x
I ...
1
vote
2
answers
56
views
Adding a Constraint to Time Series Forecasts
I have 3 variables : $X_t$, $Y_t$, $Z_t$
In my original data, for all $t$: $Z_t$> $Y_t$> $X_t$
I want to make 3 basic time series models to forecast each of these variables.
However, in the ...
0
votes
0
answers
31
views
Mismatch in # observations for predictor vs. response variables
I have a data set with only a few predictor variables (2-3) but with millions of observations. These data represent daily physical conditions for juvenile fish travelling across the ocean for a few ...
0
votes
0
answers
25
views
3-level clustering in Multilevel Latent Class Analysis of distal outcomes
I am investigating the relationship between latent classes of student experiences (also aggregated on the school level) and student achievement based on the PISA data (cross-sectional, continuous ‘...
4
votes
1
answer
113
views
Do any time series models actually assume strict stationarity?
I am taking a Time Series course, and we have covered the topic of Stationarity. The following definitions are given:
Strict Stationarity:
A stochastic process $\{X_t\}_{t \in T}$ is said to be ...
0
votes
0
answers
12
views
Question on statistical modeling for Time-Series Microbiome Data with Covariates
I'm a master's student working on an NSF-funded project investigating the impact of human visitation on island ecosystems. Our study involves three islands with varying levels of human visitation: ...
0
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0
answers
20
views
Does seemingly unrelated regressions (SUR) with the same dependent variable make sense for a time series?
SUR is a new concept to me and my advisor mentioned it and that I should explore it for my research.
I have a variable (let's call it y) that is my dependant variable. I also have 6 control variables ...
0
votes
0
answers
33
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Time series Forecast
I’ve been meaning to ask an expert in the field of forecasting a burning question about a forecasting project am working on. I’m building a model to forecast groundwater thickness, and am tasked to ...
2
votes
0
answers
49
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Books/materials about easy-to-make statistical modeling mistakes [closed]
Are there books or webpages that compile the statistical mistakes that are easy to make? Sometimes I feel like applying the fundamental models without mistakes are so much more important than learning ...
0
votes
0
answers
18
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Suggestions on what model to use (ARMA doesn't seem to be applicable)
My data looks like the following:
The ACF and PACF plots look like the following:
Although there is some dependence with some lags, I fear taking these too seriously is a form of overfitting. I don'...
0
votes
0
answers
11
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Comparing changes between two time points in ecological survey data with different survey methods
I’m working on analyzing some underwater ecological survey data, and I’m hoping to get some advice on the best statistical approach. The surveys were conducted at the same sites in 2009 and 2024, so I ...
4
votes
1
answer
95
views
Is this equation of the GARCH(1,1) model correct?
I am new to the GRACH model and have read many papers, but I am confused about the equation provided below. Is the equation (15) correct? If the $z_{t}$ is the error, why does the author define them ...
1
vote
1
answer
32
views
Propagating measurement uncertainty with posterior predictions as data in another model
I'm working on a modeling approach that incorporated estimates of measurement uncertainty trying to use brms in R. I'm working from the example in chapter 14 of ...
1
vote
1
answer
56
views
Why do the simulations of my SARIMA model not resemble my original data?
I want to simulate a SARIMA model I obtained using the auto.arima function from the R package "forecast". My objective is to be able to do a lot of simulations in order to "predict"...
1
vote
1
answer
43
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Can statistical tests be applied to analyze temperature anomalies in vaccine refrigerators across different shifts and days?
Background:
I'm analyzing the vaccine refrigerator's internal temperature data collected during COVID pandemic (2021-2022) from all over an country. I measured the internal temperature of the 1077 ...
1
vote
0
answers
51
views
In a Cholesky SVAR, why does the main diagonal of the B matrix always have identical z-scores?
Look for example at the z statistics of the B matrix on page 8 here...
https://www.stata.com/manuals/tsvarsvar.pdf
...or on page 98 here...
https://www.eviews.com/StructVAR/structvar.pdf
...or at 10:...
0
votes
0
answers
17
views
Cross-correlation function with null values
I am working on an analysis to look at features correlated with an uptrend in another feature. In order to remove noise, I've removed all dates besides where my dependent variable y is trending ...
1
vote
1
answer
22
views
Particle independence of time test
I have a series of observations of a particle positions (x_i, y_i) (let it be in 2-d), each made at time t_i using some detector ...
1
vote
0
answers
38
views
Multilevel model where skew of random effect depends on an independent variable
I am trying to construct a model where the skew of the distribution of a random effect changes with an independent variable. I'd eventually like to fit this using ...
0
votes
0
answers
23
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New to Forecasting -- Any tips for Proper Model to Use?
So I've done a ton of internet research and lost. I am trying to forecast dayrates for offshore drillships. and I have two exogenous variables that have close correlation with my historical dayrate ...
2
votes
3
answers
140
views
Time scaling of AR(1) process for modelling financial returns
Process:
Consider an AR(1) process with zero mean,*
$\lambda_t = \kappa \cdot \lambda_{t-1} + \omega_t$,
with $\kappa = 0.9$, $\omega \sim N(0, \sigma_{\omega}^2)$, and $\sigma_{\omega}^2 = 0.00027$. ...
0
votes
0
answers
41
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CausalImpact package in R - One-tailed probability
This is my first time using Bayesian statistics and the CausalImpact package in R. I'm a bit confused about whether this is using one-tail or two-tailed probability testing and was wondering if anyone ...
1
vote
0
answers
18
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Mathematical definition of a time averaged series
I am asking on how to interpret this notation. I am reading a paper discussion diffusion measurements from a mean-squared-displacement. The notation is as follows:
The main measurement is a trajectory ...
1
vote
1
answer
117
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Conditional variance from the GARCH model (using rugarch R) is just a sloping line
I'm trying to estimate the volatility of real exchange rate USD/MGA from 1970 to 2022 using the model GARCH in R.
I've been using this code and I'm not sure which part is wrong or what error I missed:
...
1
vote
0
answers
57
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Transformation w/ Rolling Regression (Residual Function)
In a time series with OLS regression curve $\widehat Y$ (rolling linear regression), and with $n=20,$ what can I say about this transformation? This formula is similar to a differential minus its ...
0
votes
0
answers
15
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Direct Multi-Step Forecasting by each day of the week?
I am looking to create a daily 7 day forecast for a particular domain problem.
Currently I have a recursive solution, which hasn't been performing too well.
I have also looked into direct forecasting ...
0
votes
0
answers
20
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Time series seasonality analysis - scoring method
I am working on the seasonal search in a time series and would like to automate the process with notations from the series, without having to manually inspect the curves. The three scores I propose to ...
1
vote
0
answers
29
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Convergence of wild bootstrap standard error to analytical HAC standard error
I'm currently estimating local projection regressions and a commonly known issue is needing to correct for autocorrelated residuals. Hence, I'm using the Newey-West HAC estimator for standard errors.
...