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Since structural time series models only require fitting process and observation error variance parameters (unlike ARIMA models, for example), the gradient of the log-likelihood function can be comput…
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I've been working on fitting a spatial autoregressive model (sacsarlm) to property price data in Córdoba, Argentina. While the model runs smoothly on smaller datasets, I've encountered an error when u…
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Assignment 2 aims to find misinformation on social network, i.e., identify profiles that
are mistakenly recorded as human/non-human profiles
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I'm trying out copilot on different topics.
For standard models, I get python code that looks valid in the examples. For models that we don't have yet (e.g. robust S-estimator) I get code that does…
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1. Linear regression
- Continuous & categorical predictors
2. Nonlinear regression (plus non-Gaussian residuals)
- Single-subject correctness sigmoids
3. Mixture models
- Model descri…
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some good packages here:
* https://adriancorrendo.github.io/tidymixedmodelsweb/code/tidymixedmodels.html#iv.-means-comparison
* https://www.r-bloggers.com/2020/08/building-anova-models-for-long-ter…
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I have been thinking for a while to add some shortcut and stripped down linear models into regression.
Stripped down means that not all functionality and results are available, i.e. "limited" models.…
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Solid start here! A couple of things:
- Are you going for inferential or predictive model? Keep in mind that for predictive modeling, linear regression is not the best option
- The tree based regr…
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ARIMA models are machine learning models which are used to predict future values of a time series based on historical data.
I am thinking of using this as a more structured and reliable form of predi…
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2024.07.22. ~ 2024.08.31. 동안 아래와 같이 학습하여 AI를 체화시키자.
- **일주일에 3개 이상씩 UCI dataset 혹은 plotly에 있는 데이터를 하나 선정하여 classification or regression을 연습할 것**
- 최소 100개의 records가 포함된 dataset
- 모델은 최소 3개 …