All Questions
Tagged with predictive-models causality
12 questions with no upvoted or accepted answers
3
votes
0
answers
1k
views
Regression: Causation vs Prediction vs Description
In my experience it seems me that the interpretation about regression, its meaning and its scope, are debatable and great confusion exist about those things. It seems me that confusions are not go ...
- 5,779
3
votes
0
answers
820
views
Implication / Interpretation of long term equilibrium VECM
I want to test the influence of exchange rates on a price index and struggle with the interpretations. My variables are I(1)
First, I ran an OLS on first differenced variables which indicated a ...
- 31
2
votes
0
answers
173
views
Confusion on Ablation test (Ablation Experiment or Ablation study)
I followed the steps of the ablation test to calculate the feature importance one by one.
In Table 1, row 1 presents the model prediction performance of using full features. Regarding rows 2-4, these ...
- 21
1
vote
0
answers
54
views
build and evaluate prediction model with the same data
I have a dataset with a sample size of n=30, one dependent variable and 31 possible predictors.
Now I want to build a regression model as part of a regression kriging model to predict my dependent ...
- 41
1
vote
0
answers
32
views
Are boosted machine learning methods robust against low probable feature combinations when predicting?
I would like to use machine learning methods in the potential outcome framework, that is, simulating outcome for all observations under different values of a specific predictor, while keeping all ...
- 2,939
1
vote
0
answers
2k
views
Evaluating results of VAR (Vector Autoregression) using R
I am trying to evaluate the results of a prediction obtained with the R function VAR. I have reproduced an example with two time series so that others can also implement it (the data set is read from ...
- 221
1
vote
0
answers
219
views
Binary logistic regression - SPSS
I did some regression analysis in SPSS using two binary variables:
Biomarker X (0= low levels; 1= high levels), where 0 was the reference category and Obesity (0=no; 1=yes)
''Biomarker X'' was taken ...
- 23
1
vote
0
answers
126
views
Do you need causal models when doing counterfactual predictions?
I am modeling the impact the number of a certain type of company (bottom of pyramid (BOP) companies, ie. companies that cater to the poorest consumers) have on market price. I considered the ...
- 11
1
vote
0
answers
299
views
Counterfactuals for Variables with Negative Values
Lets imagine I have estimated the following simple linear regression model:
$y_{i} = 10 + 0.5x_{i} + \varepsilon_{i} $, and want to work out the counter-factual, or what would $ y_{i}$ be in the ...
0
votes
0
answers
18
views
Substitution modeling under simulated inventory constraints
In the context of retail, substitution is typically defined as "when customers that prefer product A, but when unavailable, purchase product B, instead."
Naively, the most of useful ...
- 3,520
0
votes
0
answers
18
views
Extrapolating/forecasting treatment effects from difference-in-difference model
My goal is to extrapolate or forecast dynamic treatment effects into the future using a fitted model. My data consists of two groups (treated and control), seven time points, and a continuous outcome.
...
0
votes
1
answer
194
views
Difference between Predictive Inference and Causal Inference
I am looking for functional mathematical notation to explain the difference between Predictive Inference and Causal Inference? I list an example model. I also list links further down that give ...
- 1