rstanarm R package for Bayesian applied regression modeling
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Updated
May 21, 2024 - R
rstanarm R package for Bayesian applied regression modeling
an R package for structural equation modeling and more
Forecasted product sales using time series models such as Holt-Winters, SARIMA and causal methods, e.g. Regression. Evaluated performance of models using forecasting metrics such as, MAE, RMSE, MAPE and concluded that Linear Regression model produced the best MAPE in comparison to other models
An R package for Bayesian structural equation modeling
Basic statistical modelling examples.
Simple statistical prediction of the survival chances of the passengers in the testing set, given certain conditions as input. Refer to README.md for more detail
Recursive Partitioning for Structural Equation Models
Code and resources to serve as a starting point for data science projects.
農研機構統計研修「ベイズ統計モデリングとMCMC」
We present here a 1D convolutional neural network model to predict grain protein content using spectroscopic data of multiple cereals
The official implementation of "Joint Modeling of Image and Label Statistics for Enhancing Model Generalizability of Medical Image Segmentation" via Pytorch
A collection of scripts used for modeling global daily maximum surges
rstanarm R package for Bayesian applied regression modeling
2022-11_brainhack_DetecSpikMotifs: Automatic detection of spiking motifs in neurobiological data. This project aims to develop a method for the automated detection of repeating spiking motifs, possibly noisy, in ongoing activity.
A Survey on ML Techniques for Airbnb Price Prediction
OCaml Random Forests
Using data, linear regression, and statistical modeling to guide home renovation decisions.
Estimating the probability of receiving a parking ticket in San Francisco in Python
MATH-342 Time Series course taken at EPFL during Spring 17-18.
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