statistical-modeling
There are 92 repositories under statistical-modeling topic.
bambinos/bambi
BAyesian Model-Building Interface (Bambi) in Python.
yrosseel/lavaan
an R package for structural equation modeling and more
stan-dev/rstanarm
rstanarm R package for Bayesian applied regression modeling
ecmerkle/blavaan
An R package for Bayesian structural equation modeling
akshitvjain/product-sales-forecasting
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
mrtkp9993/Statistical-Modeling-Examples
Basic statistical modelling examples.
shangqigao/BayeSeg
The official implementation of "Joint Modeling of Image and Label Statistics for Enhancing Model Generalizability of Medical Image Segmentation" via Pytorch
jessecambon/Data-Science-Sandbox
Code and resources to serve as a starting point for data science projects.
ito4303/naro_toukei
農研機構統計研修「ベイズ統計モデリングとMCMC」
brandmaier/semtree
Recursive Partitioning for Structural Equation Models
adamavip/nirs-protein-prediction
We present here a 1D convolutional neural network model to predict grain protein content using spectroscopic data of multiple cereals
UnixJunkie/orf
OCaml Random Forests
mcdonohue/rstanarm
rstanarm R package for Bayesian applied regression modeling
avakanski/Rehabilitation-Assessment-through-Dimensionality-Reduction-and-Statistical-Modeling
An autoencoder neural network and a Gaussian mixture model are used for generating movement quality scores for rehabilitation exercises.
bryan-md/Data-Science-Projects
Portfolio of personal projects & curriculum from Springboard
guyabel/tidycat
Expand broom::tidy() output for categorical parameter estimates
haziqj/INLAvaan
An R package for Bayesian structural equation modeling using INLA
UnixJunkie/svmwrap
Wrapper on top of libsvm-tools
CoRE-Lab-UCF/Modeling-Global-Storm-Surges
A collection of scripts used for modeling global daily maximum surges
Mangalis0/Titanic-Survival-Conditional-Probability
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
SpikeAI/2022-11_brainhack_DetecSpikMotifs
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.
alexisrsantos/Correspondence_Lancet
Correspondence to Lancet regarding the article by Santos-Burgoa and colleagues (2018)
InPhyT/inphyt.github.io
Special repository hosting the InPhyT website.
LeondraJames/TheMatrixScript_NLP
A project utilizing NLP techniques and analysis including text mining, document term matrices, sentiment analysis, wordclouds and topic modeling with LDA.
nvlinhvn/water-consumption-campaign-analytics
Evaluate the effectiveness of water consumption campaign in 12 districts
wywongbd/EPFL-Time-Series
MATH-342 Time Series course taken at EPFL during Spring 17-18.
youheekil/Estimation-of-the-ROC-curve
Created a model to estimate the measurement error existing in ROC curves - Measurement Error model, Bernstein polynomial Model, Contaminated Non-parametric Density Estimation, MLE, EM Algorithm, R
amoustakis/Statistical-Modeling-data-analysis
A series of Statistical Modelling assignments with the use of R. Applications of Linear, Polynomial, Logistic and Poisson Regression in various datasets
b-knight/olspow
Python package for conducting power analysis for experiments using regression and/or clustered data.
Daniel-Andarge/AiML-walmart-sales-prediction-ml
This project is a machine learning competition hosted on Kaggle platform, focused on forecasting Walmart's monthly and quarterly sales. We tasked with developing advanced predictive models to accurately predict Walmart's sales, taking into account various factors such as historical sales data, macroeconomic indicators, and local market conditions.
daniel-mehta/FPL-Expected-Points
Predict Fantasy Premier League (FPL) points using two models: a Random Forest regression (ML_xP.py) and a custom statistical model (xP_FPL.py). This project explores different approaches to predicting player performance, with a detailed comparison for Gameweek 5 of the 2024/25 EPL season.
enr24/Data-Science-Academic-Projects
Attached in the repository are my academic projects from my Under Graduate Data Science Courses.
junaidali-b/projects
Data science projects created using actual data, using Python and R.
waldekmaciejko/GilbertModel
Implements in C++ Gilbert model