factor-analysis | Topic | Ecosyste.ms: Repos

Topic: "factor-analysis"

Fie-Langmann/pulses21

Analytical code for pulses 2021 data

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MWiechmann/efa_utils

Custom utility functions for exploratory factor analysis with the factor_analyzer package.

Language: Python - Size: 204 KB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

genanicole/Co-branding-between-a-fashion-brand-and-a-hotel

Co-branding between a fashion brand and a hotel

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quantmeth/SCFA

Signal Cancelling Factor Analysis (SCFA)

Language: R - Size: 191 KB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

AkanshaRajput280799/Data-Driven-Insights-into-Job-Satisfaction-and-Compensation-Trends

This project analyzes 2020 employee data to identify factors influencing job satisfaction, performance, and salary differences, offering insights for improving engagement and workplace strategies.

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veneta13/Stress-Factors

Factor analysis, PCA and cluster analysis on student stress data.

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gragusa/Factotum.jl

A Julia package for estimating static factor models

Language: Julia - Size: 44.9 KB - Last synced at: 2 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 1

NanyeonK/Factor-Momentum-Reversal-and-Turning-Point

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mtopacio35/STA-135-Project

analysis of PimaIndiansDiabetes dataset in R, utilizing multivariate data techniques of QDA, PCA, factor analysis

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juliataborek/Polish-political-scene

Language: R - Size: 19 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0

haverstein/Murder-Analysis-India

A Comparative Study and Analysis on Murders across the different states of India from 2015-2021. It looks into the patterns in motives and the possible socio economic factor affecting murder in India.

Language: Jupyter Notebook - Size: 30.9 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

jamesuanhoro/bayesianmasem

A package for Bayesian meta-analytic SEM

Language: R - Size: 17.1 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

Sharath0812/Tsunami-Data-Analysis

Objective: Analyze historical tsunami data to determine if climatic changes caused by global warming have impacted tsunami intensity or validity before and after 1900.

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gepapago/Empirical-Research

Basic methodologies of Empirical Research applied on various case studies (R language)

Size: 46.2 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

fikrianggara/Multivariate-Analysis-on-R

Source code written in R to implement multivariate analysis methods. Covering principal component analysist, factor analysist, clustering, manova, and so on.

Language: R - Size: 2.24 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

ctesta01/spearman_1904

Spearman's 1904 work on 'General Intelligence' launched the field of factor analysis into existence. This slide-deck discusses the details and aftermath.

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Kishawn-Dorman/Student-and-Client-Satisfaction-Report

first business data analysis - factors affecting student satisfaction and bank clients

Language: R - Size: 2.36 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 1

JustinKracht/noisemaker

An R package with functions for generating population correlation matrices with imperfect model fit

Language: R - Size: 385 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

tirthgala/Cluster-Analysis-for-Game-Selection

In this repository through advanced data analytics and market research assessed financial viability, customer behaviors, and market trends to form a strategic game acquisition recommendation. Process included market share simulation, cluster and factor analysis, GaborGranger pricing strategy, and customer segmentation.

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SPRstat/Analysis-of-Radiotherapy-Data

This was a course project for the course " Multivariate Data Analysis ".

Language: R - Size: 556 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

Katsuvest/Statistician

Qualifications as a Statistician

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jayjinnie/Finance-Analysis-for-Travel-Membership

2023년 신한은행 빅데이터 해커톤 | 2030을 위한 여행 멤버십 '나는 SOL로' 서비스

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VivekAgrawl/USA_Home_price_Webapp

Language: Jupyter Notebook - Size: 1.59 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

RuwaidaAl/STAT4051

Statistical machine learning techniques

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krashr-ds/medicare-analysis

Medicare DeSYNPuf analysis Gamma regression cost modeling & risk adjustment, and multiple factor analysis exposing factors associated with health care spending

Language: Jupyter Notebook - Size: 18.9 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

Palakpatel31/People_Analytics

People Analytics Project on Factors affecting Employees Performance during Covid-19

Size: 3.63 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

FabrizioMusacchio/dimensionality_reduction

Code used in blog post about dimensionality reduction using Python

Language: Python - Size: 1.43 MB - Last synced at: 2 months ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

MarioUniverseZ/fjustat_111_grproject

Language: R - Size: 370 KB - Last synced at: 2 months ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

cvas91/Composite_Indicators

Cluster Analysis Of Composite Indicators (PCA-FA)

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Fiza-Faiz/Segmentation-of-Insurance-Clients

Segmentation of the clients of an insurance company based on the survey data received from the clients. The data contains variables such as trust, experience, hospitality, service and other such customer based information. The model uses factor analysis to find the most significant factors and then used them for the Hierarchical and K-means clustering of the clients.

Language: R - Size: 5.86 KB - Last synced at: over 1 year ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

Fiza-Faiz/Service-Call-Prediction

The model tries to predict the number of sales calls that a maintenance company might be receiving based on climatic and weather conditions. The age of the car and the duration of connection with the company are also to be considered. The model tries to explore the important factors which are significant and help in getting a high accuracy of prediction.

Language: R - Size: 6.84 KB - Last synced at: over 1 year ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

sohyepargins/stats-survey-items-property-report

Examining the psychometric properties of the survey items based on the responses from the patients. IRT models (graded response model, GRMs), CFA, and EFA were used for analysis

Language: R - Size: 2.43 MB - Last synced at: over 1 year ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

hdarjus/sparvaride-matlab

Matlab Implementation of Algorithms for Sparse Factor Analyses

Language: MATLAB - Size: 27.3 KB - Last synced at: about 2 months ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 1

sainimkar/portfolio-customization

User information like age, salary, dependencies, etc are taken through a customer form and based on these factors they are classified based on risk-taking capacity. Based on this classification, this risk is correlated to generating and optimizing portfolios. Angular-flask-python

Language: TypeScript - Size: 4.01 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

rnj0nes/HCAP

Data handling and factor analysis of the Harmonized Cognitive Assessment Protocol (HCAP) neuropsychological performance battery in the 2016 Health and Retirement Study

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MattiaBrocco/R_market_analysis

Size: 93.8 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

QuizeCapital/Return.On.Invested.Capital

Return On Invested Capital - This repository contains files that demonstrate Quantitative systematic investment strategy using Return On Invested Capital as a single factor strategy.

Language: Python - Size: 5.36 MB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

LazarosAntonios/PCM-Analysis-in-R

This is a project I developed during my MSc. in UC3M. It is an R project that engages with commands on data visualisation, PCA, clustering and regression.

Language: R - Size: 2.95 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

ccrodriguez27/Assessment-of-the-Happiness-Index-of-UP-Diliman-Undergraduate-Students-using-Multivariate-Analysis

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ramprasadmohan1993/Factor-Analysis-PCA-Hypothesis-Testing

Factor Analysis/ PCA , t- test , hypothesis testing

Language: R - Size: 15.9 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

bangtedy/analisisfaktor

Repo for analisis faktor

Language: TeX - Size: 2.62 MB - Last synced at: almost 2 years ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

ecaybek/dp2fa

A simple Shiny application for preparing data to factor analysis

Language: R - Size: 21.5 KB - Last synced at: 6 months ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0

Pradnya1208/Dimensionality-Reduction-Techniques

The goal of this project is to understand and build various dimensionality reduction techniques.

Language: Jupyter Notebook - Size: 3.76 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0

daczarne/udelar_analisis_multivariado_1 📦

Análisis Multivariado I

Language: R - Size: 66.8 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0

Rutatu/experimental_methods_II

Portfolio assignments mainly focused on how the general linear model (GLM) can be used for the analysis of brain scan data. 2019 spring semester at Aarhus University

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amitesh0109/factor-analysis

Essentially conducted on a multidimensional dataset, that includes data regarding different cereal brands, and output of questions that were asked in a survey. Here, I've use PCA, which is not completely different from factor analysis, it get the jobs done. The statistics involved is basically finding different principle components and using it to deduce different factors that effects a particular cereal brand.

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