Regression
6 posts
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Building Non-Standard Regression Models with JAX
Using JAX's automatic differentiation to train a Zero-Inflated Generalised Poisson regression model
- jax
- regression
- count-data
- ZIP
- poisson
- maximum-likelihood
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Bivariate Poisson Regression with Expectation-Maximisation
Modeling correlated count data using bivariate Poisson regression with EM algorithm. Handle overdispersion and correlation in count models.
- poisson
- regression
- em-algorithm
- statistics
- python
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Cubic Spline Expansions with Logistic Regression
Flexible non-linear regression using cubic spline basis functions. Bayesian approach with PyMC for smooth curve fitting and uncertainty quantification.
- splines
- regression
- bayesian
- pymc
- statistics
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Huber Regression
Robust regression using Huber loss function. Handle outliers and improve model stability with robust statistical methods.
- regression
- robust-statistics
- huber
- machine-learning
- python
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Quantile Regression
Quantile regression for uncertainty estimation beyond the mean. PyTorch implementation for predicting conditional quantiles.
- quantile
- regression
- statistics
- machine-learning
- pytorch
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The EM Algorithm Part 2: Censored Linear Regression
Part 2: Applying EM algorithm to censored linear regression. Handle missing data and truncated observations in statistical modeling.
- em-algorithm
- regression
- censored-data
- statistics
- pymc