Create graphical goodness of fit (GOF) diagnostics from MPNet/PNet output (simulated txt files)

Limited information goodness-of-fit tests for ordinal factor models

Software companion for "Goodness-of-fit tests for the functional linear model based on randomly projected empirical processes"

📉HealthCare Dataset Statistical Analysis, Statistical Inference course, University of Tehran

Curso de Modelos No paramétricos y de Regresión impartido en la Facultad de Ciencias semestre 2026-2

R Shiny App to determine the factors that are most influential in patients’ survival of CHD. I created a Logistic Regression model in R using RStudio to predict the survival of CHD patients. Retrieved the data from the PHIS database using SQL & built tableau dashboards. The model predicted the survival of CHD with an AUC of over .90 and indicate…

Compute absolute goodness of fit via entropy estimation

Data for the reproducibility of Cuesta-Albertos et al. (2019)

Table 1 and diagnostics from complex survey designs

An example of the Monte Carlo test with the Kolmogorov Smirnov test

Statistical Modelling of Swine Flu Outbreak Data

This analysis is part of our comprehensive statistics course project. This chapter encompasses critical topics such as goodness of fit., test for independence, and contingency tables with Yates correction. These concepts are essential for examining data relationships and validating statistical models.

In this code, we will determine that whether the frequency by which car arrives as per our dataset follows a posison distribution or not using the chi-Square test.

Tests for rotational symmetry on the hypersphere. Software companion for "On optimal tests for rotational symmetry against new classes of hyperspherical distributions"

End-to-End Python scalable forensic accounting toolkit implementing Benford's Law analysis for FTSE financial data. Delivers automated anomaly detection with Chi-Squared/MAD testing, comprehensive validation pipelines, and risk-based prioritization of investigative resources. Replicates Ausloos et al.'s (2025) methodology with full reproducibility.

Group project for Statistical Inference Methods II. Moving beyond simple descriptive statistics, the study focuses on applying various hypothesis tests and inference techniques to draw specific conclusions.

Tests based on Chi-Square distribution using R.

In this we have taken a sample data to check if that data follows normal distribution or not. A hypothesis test is performed to check this using the chi-square test pf goodness of fit.