PHP implementation of statistical probability distributions: normal distribution, beta distribution, gamma distribution and more.

Replication code for simulating and estimation by GMM of DSGE models with higher-order statistics

Package provides the javascript implementation of various statistics and distribution

Study the downward bias of the root-mean-square estimator for finite samples

My Python learning experience 📚🖥📳📴💻🖱✏

Replication code for checking identification in nonlinear pruned DSGE models with Gaussian or Student's t distributed errors

Examples of generating random variables from the basic probability distributions

Examples of using the test statistics to test hypotheses

Mixtures-of-ExperTs modEling for cOmplex and non-noRmal dIsTributionS

Reproducible code for the paper “A t-distribution based operator for enhancing out of distribution robustness of neural network classifiers"

Simulation and estimation of ARCH and GARCH processes, used to model the time-varying standard deviation (volatility) of asset returns, with conditional distributions such as the normal, Laplace, and Student t.

FIt the Azzalini skew-normal and skew-t distributions to asset return data

Evaluation of the impact of stale model calibrations on tail risk estimates from the perspective of statistical backtesting.

A comparative study between 5 different binary classification techniques.

Reverse lookup for z test

Study the properties of the bivariate Student's t distribution through simulation

Background for Hypothesis testing / Bayesian Inference with code examples

Aplikasi Shiny untuk mendemonstrasikan kebutuhan akan distribusi t

Fit a Student t distribution to univariate data via maximum likelihood

Continuation to Data Analysis using more mathematical approach.

Topics covered in Probability distribution with python codes

My notes on statistics

Fit various types of Student t distributions with skew to asset returns

Analysis of historical data on childbed fever to investigate the impact of handwashing on reducing death rates. Includes data visualization, statistical testing, and time series analysis to validate Dr. Ignaz Semmelweis's hypothesis.

A Python tool 🐍 for calculating confidence intervals 📏 using the t-distribution 📊, ideal for statistical analysis with small sample sizes.

multivariate_student_t_distribution_table_generator

Aplikasi Shiny untuk membandingkan ketegaran dan kuasa uji t (klasik) dan uji Welch terhadap dua sampel.